24th Mee�ng of the European VLBI Groupfor Geodesy and Astrometry
3rd IVS VLBI Training Schoolh�p://www.oan.es/evga2019/

GOBIERNO
DE ESPAÑAMINISTERIODE FOMENTO

INSTITUTOGEOGRÁFICONACIONAL

Proceedings of the 24th European VLBIGroup for Geodesy and Astrometry
Working Meeting
17-19 March 2019
Las Palmas de Gran Canaria, Spain

edited by R. Haas, S. Garcia-Espada, and J. A. López Fernández

24th European VLBI Group for Geodesy and Astrometry Working Meeting
Las Palmas de Gran Canaria, Spain, 17-19 March 2019
Hosted by University of Las Palmas de Gran Canaria (ULPGC)

Title:
Proceedings of the 24th European VLBI Group for Geodesy and Astrometry Working Meeting
Authors:
Mentioned in each chapter
Editors:© EVGA 2019 organising committees
Rüdiger Haas (Chalmers University of Technology, Sweden). 2019
Susana García-Espada and José Antonio López Fernández (Instituto Geográfico Nacional, Spain). 2019
Edited in November 2019
Administración General del Estado Publications Catalogue:
https://cpage.mpr.gob.es

Publisher:© Present edition:
Centro Nacional de Información Geográfica (CNIG). 2019.
Design and layout:
Servicio de Edición y Trazado (IGN)(Subdirección General de Geodesia y Cartografía)
Depósito Legal: M-38563-2019
NIPO:
162-19-040-6 (paper version)
NIPO:
162-19-041-1 (electronic version)
DOI:
10.7419/162.08.2019
ISBN:
978-84-416-5634-5
Cover picture:
Poster of the 24th European VLBI Group for Geodesy and Astrometry Working Meeting
The authors are responsible for the content of their papers.
The use of the contents has to follow the laws of copyright and ownership.
This book has been printed in recycled paper.
November 2019, Madrid, Spain

CNIG: Calle General Ibañez de Ibero, 328003 - Madrid (España)
www.cnig.es – consulta@cnig.es

Preface
The 24th Working Meeting of the European VLBI Group for Geodesy and Astrometry(EVGA) was held at the University of Las Palmas de Gran Canaria (ULPGC) 17–19 March
2019. The meeting was embraced by a number of other VLBI related activities at Las
Palmas de Gran Canaria. Prior to the EVGA 2019, the 3rd IVS Training School on VLBI for
Geodesy and Astrometry was held 14–16 March. And after the EVGA 2019, the IVS Analysis
workshop, several VLBI splinter meetings and the 22nd IVS Directing Board meeting were
held on 20–21 March.
There were 114 registered participants at the EVGA2019 meeting (Figure 1) which is a
new record in the history of the EVGA working meeting (Figure 2). The participants camefrom 18 different countries, both from inside and outside Europe. Out of these 114
participants, 22 % were women. The percentage of women participating at EVGA meetings
has been increasing steadily during the last years, which is a good sign that the VLBI
community is moving forward towards gender balance.
The EVGA working meeting 2019 started with an ice breaker and registration on Sunday,
17 March, followed by the actual conference was held on Monday and Tuesday, 18 and 19
March.

Fig. 1: Picture of the EVGA 2019 participants at the campus of the University of Las Palmas de Gran Canaria (ULPGC).

I

114

120

Number of EVGA participants

100

80

60

40

20

0

2001

2003

2005

2007

2009

2011

2013

2015

2017

2019

Fig. 2: Number of participants at EVGA working meetings in the last two decades.

The participants contributed with many interesting presentations on the current status ofgeodetic and astrometric VLBI and corresponding technical development and scientific results. In total there were 52 oral presentations and 39 poster presentations. The corresponding
articles of the majority of these presentations are collected in this proceedings book. The
conference dinner on Tuesday evening closed the meeting.
We want to thank all participants for sharing their findings with the audience during interesting oral and poster presentations. We want to thank the scientific organising committee forputting together a very interesting meeting program. The program and the list of participants
are provided in Appendix-A. We are of course also grateful to all authors for preparing theirproceedings contributions. The electronic version of these proceedings will be made available
on the EVGA webpage evga.org.
The large number of participants at the EVGA 2019 Working Meeting, and the high quality
and interesting oral and poster presentations are very good indications that European VLBI
community is very active and on a good track. I am thus optimistic and convinced that we will
see a strong contribution of the EVGA to VGOS!

November 2019
Rüdiger Haas (EVGA chair)

IIMessage by José Antonio López Fernández
Subdirector for Astronomy, Geophysics and Space Applications at IGN Spain

Ten years ago, the embryo of the VGOS project (formerly known as VLBI2010), theTwin Telescope of Wettzell, started their early steps. In 2010, the IGN joined VGOS with
RAEGE, a network with four radio telescopes to be located in the Iberian Peninsula, CanaryIslands and Azores Islands. A project which means a big step forward not only for Spain, also
for VGOS and an important technical and scientific collaboration between Spain and Portugal.
RAEGE means also a firm commitment from IGN to space geodesy, trying to turn Yebes
Observatory into a GGOS Core Station, covering a big part of the Atlantic region and placing
radio telescopes in three different tectonic plates. Ten years later, RAEGE now works with theradio telescopes in Yebes and Santa Maria, Azores, and contributes with receiver technology
sharing our know-how and lessons learned with our partners at VGOS.
We are doing our best to put into operation the Artenara RAEGE radio telescope in Gran
Canaria in order to be one of the VGOS partners as soon as possible. The organization of the24th EVGA meeting in Las Palmas is one of these efforts and we can say that it has been avery definitive and important impulse for us. Now we are closer to that objective thanks to thisevent and to the help from the community. We are really proud to be organizers of a meetingthat have offered us the chance to gather the best geodetic VLBI professionals around theworld. We have been also lucky to verify how a new generation is born, as we have noticed
with its successful VLBI school, knocking on VLBI’s door and assuring the mid and longterm space geodesy in the world.
From IGN we are grateful to the EVGA chair for trusting on us, to our sponsors MT
Mechatronics, manufacturer of most of the modern VGOS radio telescopes, to the Cabildoof Gran Canaria for their support and to the impressive and excellent Las Palmas University
team. Honestly we couldn’t afford the organization of the meeting without their participation.
Let’s hold the line. All together we will achieve VGOS to be a reality soon.

November 2019
José Antonio López Fernández
Astronomy, Geophysics and Space Applications Subdirector at IGN

III

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IVEVGA 2019 organising committees
Local Organising Committee (LOC)• Susana Garcia-Espada (Chair)• Vı́ctor Araña Pulido• Esther Azcue Infanzón• Rubén Bolaño• David Cordobés Gallo• Itahiza Domı́nguez Cerdeña• Pablo Dorta• Abel Garcı́a Castellano• Yaiza Gómez Espada• Vı́ctor Puente Garcı́a

Scientific Organising Committee (SOC)• Rüdiger Haas (Chair) (Chalmers University of Technology, Sweden)• Sabine Bachmann (Bundesamt für Kartographie und Geodäsie, Germany)• Johannes Böhm (Vienna University of Technology, Austria)• Susana Garcia-Espada (Instituto Geográfico Nacional, Spain)• Laura La Porta (Reichert GmbH / Bundesamt für Kartographie und Geodäsie, Max Planck
Institute for Radioastronomy, Germany)• Evgeny Nosov (Institute of Applied Astronomy of the Russian Academy of Sciences, Russia)• Nataliya Zubko (Finnish Geospatial Research Institute, Finland)

VThis page is intentionally left blank.

VI

Contents

Technology Sessions

The Status of RAEGE . . . . . . . . . . . . . . . . . . . . .
P. de Vicente, J. A. López Fernández,
S. Garcia-Espada, R. Bolaño, L. Santos
Status of the Onsala Twin Telescopes — Two
Years After the Inauguration . . . . . . . . . . . . . . .
R. Haas, S. Casey, J. Conway, G. Elgered,
R. Hammargren, L. Helldner, K.-Å. Johansson,
U. Kylenfall, M. Lerner, L. Pettersson,
L. Wennerbäck
Establishment of a New Fundamental Site
Ny-Ålesund . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
L. M. Tangen
Efforts and Attempts to Develop VGOS-like
Stations in China . . . . . . . . . . . . . . . . . . . . . . . . . .
J. Li, C. Liu, H. Zhang, D. Zhao, Q. Fan, F. Shu,
R. Zhao, J. Wang, X. Zhang, G. Wang, X. Yang,
L. Yu, Y. Jiang, S. Guo, L. Wang
Measuring Focal Length Variations of VGOS
Telescopes Using Unmanned Aerial Systems . .
M. Lösler, C. Eschelbach, R. Haas, A. Greiwe
Instrumentation Developments for VGOS at
IGN Yebes Observatory . . . . . . . . . . . . . . . . . . . .
J. A. López Pérez, P. de Vicente,
J. A. López Fernández, F. Tercero Martı́nez,
J. D. Gallego, J. M. Serna Puente,
I. López Fernández, M. Dı́ez González,
I. Malo Gómez, C. Albo Castaño,

1

5

10

L. Barbas Calvo, O. Garcı́a Pérez,
J. González Garcı́a, B. Vaquero Jiménez,
M. Patino Esteban, P. Garcı́a Carreño,F. J. Beltrán Martı́nez, M. Bautista Durán,
J. López Ramasco, R. Amils Samalot,
G. Gómez Molina, A. Baldominos Delgado
DBBC3 Towards the BRAND EVN Receiver .
G. Tuccari, W. Alef, S. Dornbusch, R. Haas,
K.-Å Johansson, L. La Porta, H. Rottmann,
A. L. Roy, J. Wagner, M. Wunderlich
BRAND – A Wideband Receiver for
Astronomy and Geodesy . . . . . . . . . . . . . . . . . . .
W. Alef, G. Tuccari, S. Dornbusch, A. L. Roy,
M. Wunderlich, C. Kasemann, M. Nalbach,
M. Pantaleev, J. Flygare, J. D. Gallego,
J. A. López Pérez, F. Tercero Martı́nez,
G. W. Schoonderbeek, J. Hargreaves,
R. de Wild, V. Bezrukovs

27

31

12

17

22

The Stability of Delay in VLBI Digital
Backends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
E. Nosov37

A Simulator to Generate VLBI Baseband
Data in Matlab . . . . . . . . . . . . . . . . . . . . . . . . . . . .
J. Gruber, J. Böhm, A. Nothnagel, M. Schartner

42

Optical Fiber Links Used in VLBI Networks
and Remote Clock Comparisons: the
LIFT/MetGesp Project . . . . . . . . . . . . . . . . . . . . .
R. Ricci, M. Negusini, F. Perini, C. Bortolotti,
M. Roma, R. Ambrosini, G. Maccaferri,
M. Stagni, M. Nanni, E. Kravchenko,
M. Siciliani de Cumis, L. Santamaria,

47

VII

VIII

G. Bianco, C. Clivati, A. Mura, F. Levi,
D. Calonico
ITA-JPN Broadband VLBI Experiment for
Optical Clock Comparison . . . . . . . . . . . . . . . . .
M. Sekido, K. Takefuji, H. Ujihara, H. Hachisu,
N. Nemitz, M. Pizzocaro, C. Clivati,
D. Calonico, T. Ido, M. Tsutsumi, E. Kawai,
K. Namba, Y. Okamoto, R. Takahashi,
J. Komuro, R. Ichikawa, H. Ishijima,
F. Bregolin, F. Levi, A. Mura, E. Cantoni,
G. Cerretto, F. Perini, G. Maccaferri,
M. Negusini, R. Ricci
Research and Application of VLBI
Differential Phase Delays in Lunar
Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
X. Zheng, Q. Liu, F. Shu, Y. Huang, P. Li,
Z. Xu, Z. Chu
Comparison of Results Between CVN andK5 Software Correlators . . . . . . . . . . . . . . . . . . .
T. Kondo, W. Zheng, L. Liu, J. Zhang, F. Shu,
L. Tong, F. Tong
Status of the Future RAEGE Radio Telescopeat Gran Canaria . . . . . . . . . . . . . . . . . . . . . . . . . .
D. Cordobés, V. Araña, J. A. López Pérez,
A. Garcı́a, I. Domı́nguez Cerdeña, J. Ticay,
P. Dorta, I. Pérez, J. A. López Fernández,
J. Gómez González
First Steps in Gravitational Deformation
Modelling of the VLBI Yebes Radio
Telescopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A. Prudencio, E. Azcue, J. López Ramasco,
S. Garcia-Espada, Y. Gómez Espada, V. Puente,
M. Valdés
The Onsala Tide Gauge Station: Experiences
From the First Four Years of Operation . . . . . .
G. Elgered, J. Wahlbom, L. Wennerbäck,
L. Pettersson, R. Haas
VLBI-GNSS Collocation Survey at the
Ishioka VLBI Station . . . . . . . . . . . . . . . . . . . . . .
H. Munekane, M. Umei, H. Ueshiba, S.
Matsumoto, T. Wakasugi, S. Kurihara
Progress and Current Status of the VGOS
Project at the Metsähovi Geodetic Research
Station . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

N. Zubko, J. Näränen, N. Kareinen, J. Eskelinen,
M. Poutanen
52

57

62

67

71

75

80

84

Centralized Monitoring of VLBI Antennas
for Seamless Auxiliary Data . . . . . . . . . . . . . . . .
A. Neidhardt, E. Barbieri, J. Bachem,
M. Schönberger, M. S. Hameed, L. Carlin,
R. Aktas, S. Jingyao, A. Szomoru

87

Remote Access to the NASA Field System via
Web Browser . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A. Neidhardt

91

Space Low-Frequency Radio Observatory
and the Earth-Moon VLBI Experiment . . . . . .
W. Zheng, T. An, J. Zhang, L. Liu

94

An Artificial Radio Signal for VLBI Satellite
Tracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
A. Jaradat, F. Jaron, A. Nothnagel

99

The Bonn Correlator and VGOS Sessions . . . . 103
L. La Porta, W. Alef, S. Bernhart, A. Müskens,
H. Rottmann, T. Schüler, J. Wagner

IX

Observations Sessions

The EUropean-VGOS Project . . . . . . . . . . . . . . 107
W. Alef, J. M. Anderson, S. Bernhart,
P. de Vicente, J. González Garcı́a, R. Haas,
L. La Porta, I. Martı́ Vidal, A. Müskens,
A. Nothnagel, C. Plötz, H. Rottmann,
T. Savolainen, T. Schüler, D. Small, J. Wagner
Implementation of a Geodetic Path at the
JIVE Correlator . . . . . . . . . . . . . . . . . . . . . . . . . . 112
M. E. Gómez, M. Kettenis, P. Charlot,
R. M. Campbell, A. Keimpema
Activity Report on the Asia-Oceania VLBIGroup (AOV) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
T. Wakasugi
Results With the Scheduling Software
VieSched++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
M. Schartner, J. Böhm
INT9 - ∆UT1 Determination Between the
Geodetic Observatories AGGO and Wettzell . . 124
C. Plötz, T. Schüler, H. Hase, L. La Porta,
M. Schartner, J. Böhm, S. Bernhart,
C. Brunini, F. Salguero, J. Vera, A. Müskens,
G. Kronschnabl, W. Schwarz, A. Phogat,
A. Neidhardt, M. Brandl
LCONT18 - The Local Continuous
Measurement Campaign at the Geodetic
Observatory Wettzell of 2018 . . . . . . . . . . . . . . . 129
T. Schüler, C. Plötz, G. Kronschnabl,
W. Schwarz, A. Neidhardt, M. Brandl, L. La
Porta, S. Bernhart
Preliminary Work on Promoting Radar
Astronomical Study . . . . . . . . . . . . . . . . . . . . . . . 134
J. Sun, J. Ping, S. Han, F. Shu, L. Ma, W Chen,
L. CuiObservations of Radio Sources Near the Sun . 138
O. Titov, S. Lambert, B. Soja, F. Shu,
A. Melnikov, J. McCallum, L. McCallum,
M. Schartner, A. de Witt, D. Ivanov,A. Mikhailov, S. O. Yi, W. Chen, B. Xia,
M. Ishigaki, S. Gulyaev, T. Natusch, S. Weston

Autonomous Observations of VLBI Radio
Telescopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
A. Neidhardt, E. Barbieri, J. Bachem,
M. Schönberger, M. S. Hameed, L. Carlin,
R. Aktas, S. Jingyao, A. Szomoru
Mixed-mode VLBI Experiment with Chinese
Stations in APSG40 . . . . . . . . . . . . . . . . . . . . . . . . 148
X. He, F. Shu, W. Jiang, L. Ma, X. Yang,
L. ChenIntensive Sessions with the Mauna Kea
VLBA Station . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
C. Dieck, M. Davis, M. Johnson, J. Gipson,
S. Byram, D. MacMillan
Initial Analysis of IVS-INT01 Schedule
Degradation due to Added Source Flux
Catalog Latency . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
K. D. Baver, D. MacMillan, J. Gipson
HartRAO Site Tie Measurements: VLBI and
Ground Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
M. Nickola, A. de Witt, M. Schartner,
R. C. Botha, C. S. Jacobs, J. Gruber, H. Krásná,W. L. Combrinck, J. Böhm
In-depth Analysis of Schedules Optimized
for Certain VLBI Experiments Using
VieSched++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
M. Schartner, J. Böhm, A. Müskens,
A. Nothnagel, C. Plötz
A Modified Approach for Process-Integrated
Reference Point Determination . . . . . . . . . . . . . 172
M. Lösler, C. Eschelbach, S. Riepl, T. Schüler
2018 IVS Network Performance . . . . . . . . . . . . . 177
M. Bérubé, E. Himwich
CONT17 From a VieVS Perspective . . . . . . . . . 180
J. Böhm, M. Schartner

X

Analysis Sessions

The IERS Rapid Service / Prediction Centre
UT1−UTC Combined Solution: Present andFuture Contributions . . . . . . . . . . . . . . . . . . . . . . 184
M. Davis, M.S. Carter, C. Dieck, N. Stamatakos
Analysis of Intensive Sessions at BKG . . . . . . . 189
A. Girdiuk, D. Thaller, D. Ullrich,
G. Engelhardt, R. Wojdziak, C. Plötz
Scheduling of Twin Telescopes and the
Impact on Troposphere and UT1 Estimation . 194
A. Corbin, R.Haas
Comparison of Troposphere Delays from
GNSS and VLBI in R1 and R4 Sessions . . . . . . 199
V. Puente, Y. Gómez Espada, E. Azcue,
S. Garcia-Espada
An Assessment of the TroposphericParameters Estimated From the CONT17
Campaign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
T. Nilsson, K. Balidakis, T. Ning

Earth Orientation Parameters EstimatedFrom K-band VLBA Measurements . . . . . . . . . 238
H. Krásná, D. Gordon, A. de Witt, C. S. Jacobs,
B. Soja
AUA047: Students at TU Wien Organize
Their own VLBI Session . . . . . . . . . . . . . . . . . . . 243
H. Wolf, M. Schartner, J. Gruber, J. Böhm, L.
McCallum, J. McCallum, W. Hankey
Comparison of Integrated GNSS LOD todUT1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
M. Mikschi, J. Böhm, S. Böhm, D. Horozovic
Combination of IVS Intensive Sessions –Approach, Benefit, and Operability . . . . . . . . . . 252
S. Bachmann, D. Thaller, A. Girdiuk
Comparison of VLBI-based Luni-solar
Nutation Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . 257
V. Puente, J. Y. Richard, M. Folgueira,N. Capitaine, C. Bizouard
Index of authors . . . . . . . . . . . . . . . . . . . . . . . . . . . 263

Time Stability of the K-band Catalog Sources 209
K. Le Bail, A. de Witt, C. S. Jacobs, D. Gordon
VLBA Imaging of ICRF 3 Sources . . . . . . . . . . 214
L. Hunt, M. Johnson, A. Fey, J. Spitzak,
D. Gordon
The Second Version of the Bordeaux VLBIImage Database (BVID) . . . . . . . . . . . . . . . . . . . . 219
A. Collioud, P. Charlot
The Source Structure Effect in Broadband
Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
S. Bolotin, K. Baver, O. Bolotina, J. Gipson,
D. Gordon, K. Le Bail, D. MacMillan
Source Structure Effects in Next-generation
VLBI Observations . . . . . . . . . . . . . . . . . . . . . . . . 229
S. Salarpour, S. Shabala, L. McCallum,
J. McCallum, L. Chin Chuan
VLBI Analyses at the National Geographic
Institute of Spain (IGN) . . . . . . . . . . . . . . . . . . . . 234
E. Azcue, V. Puente, S. Garcia-Espada,
Y. Gómez Espada, M. Valdés

Appendices
Appendix-A:
EVGA 2019 program and participants list
Appendix-B:
3rd IVS Training School on VLBIAppendix-C:
EVGA 2019 organisation and sponsors

The Status of RAEGE
P. de Vicente, J. A. López Fernández, S. Garcia-Espada, R. Bolaño, L. Santos

Abstract The current document summarizes the statusof the RAEGE network composed of four VGOS radio
telescopes in Spain and Portugal. The radio telescopeat the observatory of Yebes is fully operational andintegrated in the VGOS core network. The station ofSanta Maria has already seen the first light and yielded
fringes with a tri-band receiver (S, X and Ka band) but
it is still under commissioning, and the other two stations have not been built yet although progress is goingon.

Keywords VGOS · IVS · Radio telescopes · Receivers

1 Introduction
RAEGE stands for Red Atlántica de Estaciones Geoespaciales (Atlantic Network of Geo Spatial Stations). It
is composed of 4 stations in Spain and Portugal. The
first operative station is located at the Observatory ofYebes in the Iberian peninsula and the second operaPablo de Vicente
Observatory of Yebes - Instituto Geográfico Nacional
Cerro de la Palera S/N Yebes, Spain
José Antonio López Fernández
Instituto Geográfico Nacional
C/General Ibañez de Ibero, Madrid, Spain
Susana Garcia-Espada · Rubén BolañoInstituto Geográfico Nacional - RAEGE Santa Maria station,
Azores, Portugal
Luis Santos
Regional Government of Azores, São Miguel, Portugal(Correspondence: p.devicente@oan.es)

Fig. 1: RAEGE stations and baselines between them.

tive antenna at the island of Santa Maria, Azores Islands. The other two, not yet built, will be located in
the Gran Canaria Island, Canary Islands and in Flores,
Azores Islands. All four stations will be become part of
the global IVS VGOS network, retaining its characteristic of being part of RAEGE network and devoting asmall fractional time for local/regional studies.
The baselines between the stations are basically
East-West, East-South West and West-South East andtheir lengths span from 600 to 2400 km. Fig. 1 shows
the baselines on a map.
The four stations are located on three different
plates (see Fig. 2): the Eurasian, the African and
the American one. The strategic distribution of thestations will allow to determine relative movements ofthe plates as a function of time. Observations within
VGOS or dedicated ones will serve for this purpose.

2 The Yebes station
The Yebes VGOS station (Fig. 3) was built in 2013 andit is in operation as a VGOS telescope equipped with1

2de Vicente et al.

Fig. 2: RAEGE stations superposed on a physical map with plateborders.

a broad band receiver (2 − 14 GHz) since April 2016.
It is one of the seven current core VGOS stations andit has taken part in tests along 2016, 2017, 2018 and2019. The periodicity of the observations since 2017 is
14 days, lasting 24 hours for each observation. In 2017
we took part in 24 observations, whereas in 2018 we
took part in less observations (19) due to a mechanicalerror at the antenna and in 2019, by the time of thisreport, we have already observed 11 times.
Yebes is also taking part in the EU-VGOS initiative, see Alef et al. (2019), as one of the three core
European stations. The observations take place every
15 days and precede the VGOS sessions. These observations last a few hours and are used for testing several parts of the overall process which encompasses
scheduling, observing, correlation, fringe fitting, analysis and data archiving.
The broad band receiver installed at the telescope
was designed and built at the Observatory of Yebes.
The system temperature is 50 K in average, being below that value at frequencies where no RFI is present.
RFI is a severe problem at the site and to avoid saturation of the LNAs and of the optical fiber amplifiers ahigh band pass filter at 3 GHz was installed. Besides,
to protect the optical fiber system a 6 dBm PIN diodepower limiter is in place. The behaviour of the receiver
has improved substantially after these two measures,
which mitigate the RFI, were implemented.
Since 2017 the telescope has used 4 RDBEG backends and one Mark6 recorder and generates data incomplex format. Four down conversion modules built
at the Observatory of Yebes are in place before each
RDBEG. The down conversion units with tunable local oscillators, yield two IF signals 500 MHz bandwidth, each in the selected frequency interval, acrossFig. 3: Yebes 13.2 m station with the 40 m in the background.

the VGOS wide band. VGOS data are transferred using disk packs to Haystack correlator except in the lastepoch when they have been transferred via Internet. All
EU-VGOS are transferred via Internet to Bonn correlator.
The Observatory of Yebes is a Technological Development Center for the IVS and it performs a number of works which are described in López Perez et al.
(2019). The main tasks are related to the developmentof cryogenic active (amplifiers) and passive devices,cryogenic receivers, and the improvement of the geodetic phase cal system.
The Yebes Observatory will become soon a geodetic core station after the future installation of a SLR
telescope. This telescope together with the current two
GNSS antennas (one in the international network andthe second in a national network), the gravimeters andthe VGOS radio telescope, will provide coordinates indifferent reference systems. A local tie composed of
23 concrete pillars connects all the previous points andprovides the local link between the different reference
systems.
In the future a correlator will be deployed at theObservatory of Yebes for the RAEGE network. We arealso developing an analysis group at the IGN headquarters which has started processing legacy IVS data using WHERE software from NMA and VIEVS from the
University of Vienna.

The Status of RAEGE

3

3 The Santa Maria station

4 The Gran Canaria station

The Santa Maria station (see Fig. 4) is located at Santa
Maria island at an altitude of 240 m. The first single
dish observations at Santa Maria station took place in2017 and the first fringes were obtained in 2018 (seeFig. 5).

The local government of Gran Canaria granted in 2018the usage of a terrain for the construction of the future
VGOS radio telescope and the control building. The
site is at 1100 m of altitude and in a natural protected
area. The strict requirements needed to protect the local
environment have delayed the construction for a very
long time. Meanwhile funds for all previous civil works
have been secured and the administrative paperwork is
being sorted out to be able to start the conditioning of
the site by late 2019, since construction works are prohibited between March and September for environmental reasons.
The antenna, already built by MT Mechatronics, isstored in a warehouse at Gran Canaria island and undergoes periodic inspections until it gets installed at its
definitive site.
The Observatory of Yebes has deployed two people
at Gran Canaria to track the progress of the station. The
agreement between the IGN and the University of Las
Palmas of Gran Canaria to provide technical support tothe telescope has allowed to host the IGN staff at thepremises of the university. Part of the future technicalworks will be done together with the University.

The radio telescope is equipped with a tri-bandreceiver that covers S band (2 − 2.7 GHz), X band
(7.5 − 9 GHz) and Ka band (28 − 33 GHz), with system temperatures close to 50 K in average. The receiver
was built at the Observatory of Yebes and it is similar
to the ones installed at Ishioka and Ny-Ålesund. It allows to perform legacy IVS VLBI observations. The
data acquisition system is a DBBC2 and the recording
system a Mark5B+. There is a second Mark5B+ at thestation for transferring data to the correlator. The Internet connection has a low data rate, 80 Mb/s, whichallows transfers but prevents high speed connections.
Some legacy IVS observations in tag-along mode
have been performed in 2018 and 2019 but several
problems with the antenna and the receiver have prevented a continuous operation of the station. The issues
are still being worked out.
The broad band receiver for Santa Maria is alreadybuilt and pending of tests at the Observatory of Yebes.
The installation date at the antenna will depend on
the availability of VGOS backends and the broad band
donwconversion system.

5 The Flores station
The Flores station is the least developed one of the
RAEGE network. The administrative paperwork to get
the ownership of the terrains has started. This station
will be fully funded by the Regional Government of
the Azores.
The soil conditions are being evaluated and the
RFI environment was measured some years ago.
Currently the weather conditions are being analyzed
since the location shows strong and frequent winds.
This condition should be taken into account in thedesign of the radio telescope to prevent corrosion anddifficulties in the operation and maintenance of thetelescope.

Fig. 4: Santa Maria 13.2 m station from a drone.

4de Vicente et al.

Fig. 5: A fourfit plot with X band fringes between the Santa Maria 13.2 m station and the 40 m radio telescope at Yebes.

References
Alef W, Anderson J M, Bernhart S., et al. (2019) The
EUropean-VGOS Project. In: R. Haas, S. Garcia-Espada,J. A. López Fernández (eds.): Proc. 24th EVGA Working

Meeting, 107–111
López Perez A, de Vicente P, López Fernández J A, et al.
(2019) Instrumentation Developments for VGOS at IGN
Yebes Observatory.
In: R. Haas, S. Garcia-Espada,J. A. López Fernández (eds.): Proc. 24th EVGA Working
Meeting, 22–26

Status of the Onsala Twin Telescopes — Two Years After the
Inauguration
R. Haas, S. Casey, J. Conway, G. Elgered, R. Hammargren, L. Helldner, K.-Å. Johansson, U. Kylenfall,
M. Lerner, L. Pettersson, L. Wennerbäck

Abstract We give a brief overview on the status of
the Onsala twin telescopes (OTT), two years after theirinauguration. The different components of the VGOS
systems are briefly described, and the development towards routine operations.

Keywords VGOS · Onsala twin telescopes · DBBC3

1 Introduction
Fig. 1: The Onsala twin telescopes at night, with OW (left) and

The Onsala twin telescopes (OTT) (Fig. 1) are two
identical VGOS telescopes that were designed by MT
Mechatronics GmbH. The OTT were installed during
2015/2016 in a distance of 75 m from each other.
The ceremonial inauguration took place in May 2017
in connection to the 23rd Working Meeting of theEuropean VLBI Group for Geodesy and Astrometry(EVGA) (Haas et al., 2019). Within the International
VLBI Service for Geodesy and Astrometry (IVS) the
OTT are known as ONSA13NE and ONSA13SW, with
2-character abbreviations OE and OW, respectively.
The telescopes have a ring-focus design with a mainreflector diameter of 13.2 m. As all VGOS telescopes
they have fast slewing speeds: 12 and 6◦ /s in azimuthand elevation, respectively. The RMS surface accuracyRüdiger Haas · Simon Casey · John Conway · Gunnar Elgered · Roger Hammargren · Leif Helldner · Karl-Åke Johansson · Ulf Kylenfall · Mikael Lerner · Lars Pettersson · Lars Wennerbäck
Chalmers University of Technology, Department of Space, Earthand Environment, Onsala Space Observatory, SE-439 92 Sweden(Correspondence: rudiger.haas@chalmers.se)

OE (right). Photo taken by Armin Corbin in early 2019.

of the main reflectors was determined to be 82 µm and102 µm for OE and OW, respectively (Lösler et al.,2017), which is fulfilling the VGOS requirements.

2 The signal chain
The OTT are equipped with cryogenic broadband
receiving systems that were built at Onsala and areto a large degree identical (Pantaleev et al., 2017a).
However, they have two different feed horns. OW isequipped with an Eleven-Feed of type 2017EFiC-214C-8P. It has hybrid couplers to reduce the needed
number of low noise amplifiers from eight to two.
The design is compact and wide band, with an opening angle of 65◦ , dual linear polarized covering afrequency range of 2 − 14 GHz. The intention when
designing the system was to achieve compatibility
with the legacy S/X systems. OE is equipped with a
Quad-Ridged Feed Horn (QRFH) that was purchased
56

The OTT use one DBBC3 backend (Tuccari et al.,2018) each. These DBBC3s are of type DBBC3-8L8H,
i.e. equipped with 8 IF-modules with 4096 MHz bandwidth each. There are eight analogue conditioning
modules, called GCoMo, each covering 4 GHz of
RF-input. The RF-signals are fed into the DBBC3s
according to Tab. 1. Since the highest frequency band
(11.4 − 15.2 GHz) is not yet used for VGOS test
observations, RF-band (3.8 − 7.6 GHz) is currently
split and fed into the two middle modules. However,Table 1: RF input to the DBBC3s. For the current VGOS test experiments, Band-3 and Band-4 are fed with the same frequency
range. However, all systems are prepared to be fed with a higher
frequency band (red) in the future.
OW - Eleven-Feed
OE - QRFH
RF-band Bandwidth (GHz) Bandwidth (GHz)Band-1
2.0 – 3.8
3.0 – 3.8
Band-2
3.8 – 7.6
3.8 – 7.6
Band-3
3.8 – 7.6
3.8 – 7.6
Band-4
7.6 – 11.4
7.6 – 11.4
(11.4 – 15.2)(11.4 – 15.2)

3 Pointing and sensitivity
Soon after the official inauguration in May 2017, firstlight was achieved with both OTT and radio source
signals could be detected. Following this, during thesummer of 2017 the work continued to derive pointing models. Fig. 2 depicts the current level of pointing
residuals for both telescopes. The RMS residuals for
OE are 14.8 arcsec and 10.3 arcsec in elevation (E) andorthogonal to elevation (xE), and for OW 15.6 arcsec
and 13.2 arcsec, respectively.
OTT-N pointing 201975

50

residual E (arcsec)

The backends are located in the observatory control room at the 20 m radome enclosed telescope, approximately 500 m straight line distance from the telescopes. The radio frequency (RF) signals are sent fromthe telescopes via optical fibres which are approximately 1 km long since they are burried 70 cm below the soil surface and cannot follow the straightline. The cable length variations are monitored with cable delay measurement systems (CDMS). Each of thetelescopes is equipped with four RF-over-fibre (RFoF)
transmitters each located on the receiver trolley, twofor vertical and two for horizontal polarization. Dueto a high level of radio frequency interference (RFI)in the lower end of the frequency range and potential problems with saturation, the polarizations are split
into a low (2.0 − 6.0 GHz) and a high frequency part(3.8 − 18.0 GHz). The corresponding RFoF receivers
are located in the control room, close to the backends.

the systems are prepared to cover higher frequencies
in the future, see the range marked in red in Tab. 1.

25

0

-25

-50

-75
-75

-50

-25

0

25

50

75

50

75

residual xE (arcsec)
OTT-S pointing 201975

50

residual E (arcsec)

from Caltech. The type is QRFH-60S-6-3 which
was customized for an opening angle of 60◦ and afrequency range of 3 − 18 GHz. The intention when
designing this system was to avoid the RFI-polluted
lower S-band frequencies. The two receiving systems
are interchangeable so that both OTT should be able toco-observe in mixed-mode with legacy S/X systems,
however, not simultaneously.

Haas et al.

25

0

-25

-50

-75
-75

-50

-25

0

25

residual xE (arcsec)

Fig. 2: Pointing residuals for OE (top) and OW (bottom).

Status of the Onsala Twin Telescopes

7

In the autumn of 2017 first interferometric tests
were done. In a test on 25 September, fringes were
found for some RF bands for OE, and on 5 Octoberalso for OW. Both systems were adjusted and finallyon 13 November 2017 fringes were found in all 4 RFbands for OE. It took until 8 February 2018 before thesame was achieved with OW.
Extensive measurements were performed to characterize the OTT system performance at the frequencies currently used for VGOS test sessions. Fig. 3
depicts system equivalent flux density (SEFD) measurements. In general, except for the lowest frequency
range, around 3.0 − 3.5 GHz, which is affected heavily
by RFI disturbances, the goal of 2000 Jy is achieved
with both systems. However, there are also RFI around
5.2 GHz and 5.8 GHz for horizontal polarization.
A complete monitoring of the broadband sensitivity, i.e. not only the current VGOS frequencies, isplanned for the future.

4 Data recording and transfer
The OTT use Flexbuff computers as recorders. Currently there are two such machines, with 330 TB and
432 TB storage capacity, respectively. The backend
systems can be flexibly connected to any of therecorders. Extensive tests have verified that recordingsof up to 50 Gb/s are possible. Fig. 4 gives an overview
of the current connectivity of the OTTs. The connectivity to the outside world is using two 10 Gb/s links,
but can easily be upgraded to 100 Gb/s if necessary.

OW

OE

32 fibres

32 fibres

DBBC3 #1

2 x 32 Gb/s

DBBC3 #2

Mellanox SN2410
48 x 25 G + 8 x 100 G

2 x 32 Gb/s

7000
H-pol
V-pol

6000

Flexbuff #1

RFI

SEFD (Jy)5000

Flexbuff #2
2 x 10 Gb/s
to the world4000

red = 100 Gb/s fibres

two Flexbuffs have currently 330 TB and 432 TB storage capacity, respectively.

2000 Jy
2000

1000
3000

blue = 10 Gb/s fibres

Fig. 4: Schematic overview of the OTT network connection. The

3000

5000

7000

9000

11000

frequency (MHz)5 VGOS operations

3000

SEFD (Jy)

H-pol
V-pol

We are very thankful to Ed Himwich for his support tointegrate the DBBC3 control into the VLBI Field System (FS). The OTT operations can now be performed
completely with the Field System FS 9.12.12 VGOS
branch. This includes:

2000 Jy
2000

1000
3000

5000

7000

9000

11000

frequency (MHz)Fig. 3: SEFD measurements for OE (top) and OW (bottom).

• configuration of the DBBC3 backends• direct communication with the antenna control
unit• control of data recording• control of the cable delay monitoring system(CDMS), including phase cal (PCAL)

8

There is one FS per OTT-system. They are interchangeable and can be accessed remotely. The telescopes themselves can be monitored via live-feed cameras, both in the control room as well from the outside. Additional monitoring of numerous telescope status parameters is possible via the in-house software”Bifrost”. The data recording is monitored during observations with spectra and sampler statistics information that are displayed graphically on the FS screen.
During 2017, we participated in 6 VGOS test (VT)sessions of 24 h length, either with one or both systems.
The VT-sessions are observed currently with 8 Gb/s
and are correlated at Haystack observatory. There were
problems with weak fringes and the level of the phasecal signals, so that no useful VGOS databases resulted.
In 2018 we participated with OE in total in 18 of
the 24 h VT sessions. One of these sessions was observed with both OTTs. While the PCAL situation
improved during 2018, there were problems with the
DBBC3s. These problems caused data loss and no
VGOS databases could be produced. In 2018 a lotof work was spent on improving the stability of the
DBBC3s. Finally, the last VT-session in December
2018, which was also observed with both OTTs, wasproblem-free. Besides the international VT-sessions,
we also observed with OE in 10 shorter sessions (4–6 h) with the European VGOS partner stations Wettzell
and Yebes. These European VGOS (EV) sessions arecorrelated in Bonn. We also observed 6 sessions of various observation length together with Kashima, the socalled OK-sessions with different frequency setup than
the standard VT-sessions and 16 Gb/s recording. A listof the 2017/2018 observations is provided in Haas etal. (2019b).
After the steep learning curve in 2017/2018
with continual system improvements, the situation
became stable in early 2019. We participate in boththe bi-weekly VT-sessions as well the EV-sessions,and the performance is in general good and stable.
The first VGOS databases that could be analysed are
19JAN07VG and 19JAN222VG.

6 Further aspects
During the summer of 2018 a photogrammetric surveyof OE was performed with an unmanned aerial vehicle (UAV). The aim was to investigate the elevation-

Haas et al.

dependent variations of the focal length (Lösler et al.,2019a) and to derive a model for signal path variation(SPV) in the telescope optics due to gravitational deformation (Lösler et al., 2019b).
The OTT were also equipped with a temperatureand humidity monitoring system. Temperatures aremonitored in different levels and directions in thetelescope towers, inside the telescope azimuth andelevation cabins, and at various places along theoptical fibres.
Furthermore, a local geodetic survey network with
6 concrete pillars was established around the OTT anda first epoch survey was performed (Heep, 2018). Thisis the basis for a classical local-tie survey which isplanned for 2020.
In early 2019 first short baseline interferometry
measurements were performed between the OTT and
ON, the Onsala 20 m telescope, using X-band observations (Marknäs, 2019), see Tab. 2.
Table 2: Baseline length (L) and standard deviation (σ) in theOnsala telescope cluster, derived from local interferometric measurements at X-band performed in early 2019 (Marknäs, 2019).
Baseline
L (m)σ (mm)OE - OW
74.9612± 0.2
OE - ON468,6819± 0.5
OW - ON
540.3115± 0.4

7 Conclusions and outlook
A little less than two years after their official inauguration the OTTs have become operational. They areused operationally on a regular basis for VGOS observations. Data observed in the IVS VT-sessions are sent
to the correlator at Haystack observatory and VGOS
databases for post-processing are produced. Data observed in the European EV-sessions are sent to the correlator at Bonn. The plan is to continue to contribute to
VGOS observations, both on the international and theEuropean level.
One important aspect for the upcoming months will
be to start to also observe in the so-called mixed-mode,using both the OTT and the Onsala 20 m radio telescope that is used for IVS S/X legacy observations.
Further steps are to do additional local interferometry
observations with the Onsala telescope cluster and toStatus of the Onsala Twin Telescopes

perform a classical local-tie survey and determinationof the reference points.
On the system level, work will continue to fine-tune
the pointing models, to derive gain curves, and to calibrate the OTT.

References
Haas R, Casey S, Elgered G, et al. (2019) Status of theOnsala Twin Telescopes – One Year After the Inauguration. In: K. L. Armstrong, K. D. Baver, D. Behrend (eds.):
IVS 2018 General Meeting Proceedings, NASA/CP-2019219039, 17–19
Haas R, Hobiger T, Elgered G, et al. (2019) Onsala Space Observatory – IVS Network Station Activities during 2017–2018. In: K. D. Baver, D. Behrend, K. L. Armstrong(eds.): International VLBI Service for Geodesy and Astrometry 2017+2018 Biennial Report, in press
Heep N (2018) Erweiterung des terrestrischen Kontrollnetzes derTwin-Teleskope an der Fundamentalstation Onsala. Bachelor thesis, Frankfurt University of Applied Sciences, 66 pp.
Lösler M, Eschelbach C, Haas R (2017) Unified model for surface fitting of radio telescope reflectors. In: R. Haas, G. Elgered (eds.): Proc. 23rd EVGA Working Meeting, 29–34

9Lösler M, Eschelbach C, Haas R, et al. (2019a) Measuring
Focal-Length Variations of VGOS-Telescopes Using Unmanned Aerial Systems. In: R. Haas, S. Garcia-Espada,J. A. López Fernández (eds.): Proc. 24th EVGA Working
Meeting, 17–21
Lösler M, Haas R, Eschelbach C, et al. (2019b) Gravitational
Deformation of Ring-Focus Antennas for VGOS – First Investigations at the Onsala Twin Telescopes Project. J Geod,
doi:10.1007/s00190-019-01302-5
Marknäs V (2019) Connecting the Onsala Telescope Cluster Using Local Interferometry. Master’s thesis, Departmentof Space, Earth and Environment, Chalmers University ofTechnology
Tuccari G, Alef W, Dornbusch S, et al. (2018) DBBC3 – the new
wide-band backend for VLBI. In: Proceedings of Science,
344, 14th European VLBI Network Symposium & Users
Meeting (EVN 2018), doi:10.22323/1.344.0140
Pantaleev M, Haas R, Billade B, et al. (2017) Onsala Space Observatory – IVS Technology Development Center Activities
during 2015–2016. In: K. D. Baver, D. Behrend, K. L. Armstrong (eds.): International VLBI Service for Geodesy andAstrometry 2015+2016 Biennial Report, NASA/TP-2017219021, 301–305
Pantaleev M, Helldner L, Haas R, et al. (2017) Design, Implementation and Tests of the Signal Chain for the Twin Telescopes at Onsala Space Observatory. In: R. Haas, G. Elgered(eds.): Proc. 23rd EVGA Working Meeting, 15–19

Establishment of a New Fundamental Site Ny-Ålesund
L. M. Tangen

Abstract We started to build the first part of theroad and bridge in 2013. The rest was done in 2014.
Veidekkearctic did the construction work from Oct.
2014 to Oct. 2015. Both telescopes arrived April 2016.
GNSS, DORIS and Gravity is in operation. Tests with
Tri-band-feed are done and the first broadband feed
will arrive summer 2019.

at Svalbard, during the winter can be a challenge, but
Veidekke did this very well.

Keywords Road · Bridge · Telescope

In spring 2015, the VLBI towers were finished andthe local tie fundaments were done. The local tie fundaments are made as a tripod. Three steel pipes are drilled
down in solid rock. They are frozen with water in thepermafrost. Logging of the stability is done, and all tripod fundaments are not stabile enough. We have mademore fundaments with one H formed steel pole. They
are better.

1 Start up

All buildings (station, gravity, SLR and walkways)
and all geodetic fundaments were finished and delivered to Kartverket Oct 2015.

We started summer 2013 with building the road half
the way and a bridge. During the summer, a ship cameand put the new fiber optic cables from Longyearbyen
to Ny-Ålesund on the seabed.
Next summer the rest of the road was made and thestation area was prepared for construction work.
Veidekke Arctic got the contract and they started up
autumn 2014 with all fundaments for the buildings andthe geodetic equipment.
The most exciting part was how deep we had to
dig down for the VLBI fundaments. Test drillings said
4 meters and that was correct.
The construction work had to be done during thewinter. The Governor of Svalbard had this as a part oftheir permit to build. To do construction work outside
Leif Morten Tangen
Norwegian
Mapping
Authority,
Geodetic
Kartverksveien 21, Hønefoss, NO-3511 Norway(Correspondence: Leif.Morten.Tangen@kartverket.no)

Institute,

2 Technical solutions
The station has to power systems. A UPS system withgenerator and the standard one. The UPS is made for
critical systems as maser and cooling only. It is not possible to move the telescopes when the station run on
UPS/generator.
To keep all signal cables from technical room to
the receiver as stable as possible, they have an own insulated and heated box in the walkways.

3 Telescopes
The telescopes arrived Ny-Ålesund in April 2016 anddelivered to Kartverket in September from MT Mechatronics.
10

New site Ny-Ålesund

11Fig. 1: The new station in winter

4 Other things• Maser (T4 Science) in operation June 2016
• Tri-band feed from Yebes for tests in NS (NyÅlesund South)• ACS from Yebes for antenna control• Backend: DBBC3 and Flexbuff• First broadband feed from Yebes summer 2019
• SLR 2022
• GNSS in operation Nov 2015
• Local tie• DORIS about 400 m away, connected with local
tie• Constructor blogg http://veidekkearctic.no/

5 Other challenges• Lack of VGOS correlation capacity• Test of full VGOS not possible• Lack of up to date development plan for VGOS
operation/analyzing capacity• VGOS HW/infrastructure must be built to matchthe development plan in item 3.

• Operational cost of the Observatory in standby
without observing is about 100 k€.
• Damaging for geodetic activities not to fully utilize
the Observatory due to lack of international correlation capacity

6 Opportunities
Take a closer look to this link and check if you
can send an apply for support: https://ec.europa.
eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/infradev-01-2019-2020;
freeTextSearchKeyword=;typeCodes=1;statusCodes=
31094501,31094502;programCode=null;programDivisionCode=null;focusAreaCode=null;crossCuttingPriorityCode=null;callCode=Default;sortQuery=deadline;orderBy=desc;onlyTenders=false;topicListKey=
topicSearchTablePageState

Efforts and Attempts to Develop VGOS-like Stations in China
J. Li, C. Liu, H. Zhang, D. Zhao, Q. Fan, F. Shu, R. Zhao, J. Wang, X. Zhang, G. Wang, X. Yang, L. Yu,
Y. Jiang, S. Guo, L. Wang

Abstract The development of the China VLBI network(CVN) is reviewed in this presentation, especially concerning the efforts and attempts to develop new stations of the VLBI Global Observation System (VGOS),
the next generation radio telescopes for astrometry andgeodesy.

Keywords VLBI · CVN · VGOS · Radio telescope ·Astrometry · Geodesy

1 Introduction
In contrast to satellite-related techniques such as Satellite Laser Ranging (SLR) and Global Navigation Satellite Systems (GNSS), Very Long Baseline Interferometry (VLBI) is outstandingly characterized in several
aspects. The measurement of VLBI is not detrimentally affected by the uncertainties of Earth gravity fieldmodel, nor the motion of the Earth center. VLBI precisely determines the relative position / direction of observation stations and targets. VLBI observation is in
the radio frequency domain and so is available roundthe clock and in almost all the weathers except ex-tremely bad ones such as typhoon, heavy rain or snow.
The extragalactic radio sources (ERS) of several billions of light years are almost fixed onto the deep spacebackground of the Universe. By taking ERS as referencing target, VLBI determines the relative uncertainty of baseline length up to 1 ppb (1E-9) or better on
the global scale and with extremely high long stability.
VLBI determines all the dimensions of Earth Orientation parameters (EOP) including UT1, polar motion
and corrections to nutation / precession model, precisely ties the terrestrial reference frame (TRF) withthe celestial reference frame (CRF).
In this presentation, it is described from the pointof view of the authors about the efforts and attempts
to develop stations of the VLBI Global Observation
System (VGOS) in China. Section 2 presents a brief
overview of the China VLBI Network for astrometry
and geodesy (CVN). Section 3 presents a descriptionof the current situation to develop VGOS-like stationsin China. Section 4 describes some considerations on
the development of new VGOS stations. Section 5 concludes the presentation with some discussion on futurework.

2 Overview of the CVN development
Jinling Li · Cong Liu · Hui Zhang · Daxin Zhao · Qingyuan
Fan · Fengchun Shu · Rongbing Zhao · Jinqing Wang · Xiuzhong
Zhang · Guangli Wang · Linfeng Yu · Yongbin Jiang · Shaoguang
Guo · Lingling Wang
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
Xuhai Yang
National Time Service Center, Chinese Academy of Sciences,
Lintong, Xi’an 710600, China(Correspondence: jll@shao.ac.cn)

The key techniques sustain the high precision operation performance of VLBI mainly include the followings. The progressive improvement in data recording
rate from kilo-bits per second (k bps) to mega- andto gigabits, and from single to multi channels, whichsignificantly increases the technical sensitivity. The invention of the bandwidth synthesis technique, which
achieves equivalent delay precision of wide frequency
12

VGOS-like Stations in Chinaband by synthesizing the data from multi-narrow frequency channels. If the whole wide band was sampled,
quantized and recorded, the data volume would behuge and so be costing much more recording medium.
And if only a narrow band was recorded, the delay
uncertainty would be relatively large. The Hydrogenmaser which is essentially high in frequency stability, permits those remote stations individually and synchronously collecting the interferometry data which
could be centrally correlated following the observation
sessions. The advanced receiving device of low equivalent noise temperature permits the high technical sensitivity. The sophisticated astrometric and geophysicalmodels and the improved methods of observation dataprocessing contribute the high quality and precision of
VLBI products.
In China the VLBI technique development started
from early 1970s. An experimental system of radio
telescope was constructed at Shanghai Astronomical
Observatory (SHAO), Chinese Academy of Sciences(CAS) in 1974. As shown in Fig. 1 (a), the diameter of
the antenna is 6 m. With this system some international
VLBI experiments were initiated by cooperation withfor instance the 100-m telescope at Effelsberg in 1981
and the 26-m telescope at Kashima in 1985 (Wan et al.,1983, 1987; Heki, 1995; Li et al., 2010).
The Sheshan 25-m antenna system (Fig. 1 (b)) at
Shanghai is the first modern radio telescope in China,
which participated in VLBI observation from 1987 (Liand Wang, 2001). The Nanshan 25-m radio telescope at
Urumqi (Fig. 1 (c)) performed observation from 1994.
The two 25-m antennas are the network componentsof the International VLBI Service for astrometry andgeodesy (IVS) and the reference stations in the International Terrestrial Reference Frame (ITRF). They alsosignificantly improve the U-V coverage of the European VLBI network (EVN).
In 2000, a mobile VLBI station was constructed by
SHAO for the Xi’an Surveying and Mapping Institute.
The station is located at Yunnan Astronomical Observatory, Kunming, China. It is a 3-m antenna system andhad contributed to the China Lunar Exploration Project(CLEP) in the experimental observation phase.
Directly promoted by CLEP, in 2006 the Miyun
50-m antenna at Beijing (Fig. 1 (d)) and the Phoenix
Mountain 40-m antenna at Kunming (Fig. 1 (e)) werecommissioned and the SHAO VLBI correlation center
began routine operations (Hong, 2007). Due to the further requirements of China’s subsequent lunar and deep

13

Fig. 1: The CVN radio telescopes.

space exploration, the Tianma 65-m radio telescope atShanghai (Fig. 1 (f)) was essentially constructed by theend of 2012 (Li et al., 2014). The current observation
bands cover L, S, C, X, Ku, K, Ka and Q.
We also have several radio telescopes for deep
space exploration in China, for instance the 35-m at
Kashi and the 64-m at Jiamusi. Now we are developing some broadband VLBI (VGOS-like) stations
for astrometry and geodesy as well as for satellite
navigation.

3 VGOS-like stations in China
Since 1980s the conventional VLBI observation for astrometry and geodesy has been at S/X dual frequency
bands, centered at about 2.3/8.4 GHz. With the progressively wide application of radio frequency active
emission in national defense, economy development
and daily life, the radio interference to the passive reception of astrometric and geodetic VLBI observation
at S-band becomes more and more serious. In addition
to the rapid development of electronic technology andthe increasing demand of accuracy for astrometric andgeodetic VLBI products, the technical specifications
were recommended for the next generation radio telescopes for astrometry and geodesy (Petrachenko et al.,2009).
We have roughly three types of VGOS-like stations with different systematic designs and technical

14

Li et al.

Fig. 3: Pictures of the Sheshan13 telescope.

3.3 Sheshan13
Fig. 2: Pictures of the Tianma13 telescope.

specifications, supported by different institutions and/ or through different projects. Type I, NTSC13, National Time Service Center (NTSC), CAS. Type II,
Tianma13, SHAO, CAS. Type III, Sheshan13, SHAO,
CAS. The antennas are all about 13 m in diameter, withhigh slew rate as 12 ◦ /s in azimuth and 6 ◦ /s in elevation.

3.1 NTSC13
The frequency band of NTSC13 is 1.2 GHz ∼ 9 GHz.
The efficiency is higher than 50 %. The equivalent temperature of the receiver is about 70 K. There are threestations of NTSC13 located at Kashi, Changchun andSanya, mainly for the corrections of systematic uncertainties in the tracking / positioning of navigation satellite.

In Fig. 3, the left panel is a satellite map of the yardof Sheshan 25-m antenna, the Sheshan13 is at the leftupper corner. The broadband receiver of Sheshan13 is
2 GHz ∼ 14 GHz with typical equivalent temperature
as 18 K. The dual band X/Ka receiver is 7 GHz ∼9.5 GHz / 28 GHz ∼ 34 GHz and the equivalent temperature as 15 K / 25 K. The data recording is 4 channels of bandwidth 512 MHz and would be updated to
1 GHz.
Fig. 4 shows the system temperature (T sys ) of Sheshan13. The broadband is about 40 K but contaminatedby many interference signals below 6 GHz and at about
13 GHz. The dual band frequency is down converted to
3 GHz ∼ 12 GHz. The system temperature at X-band
is about 30 K and at Ka-band about 60 K. Table 1 lists
out the aperture efficiency and the system equivalent
flux density (SEFD) at various frequencies and at elevation about 50◦ . For the broadband the typical aperture efficiency is above 50 % and the SEFD is about
1600 Jy. On 14 September 2018 we got the first fringeat broadband between Sheshan13 and Tianma13. Fig. 5
shows a recent fringe example. We are planning to join
in VGOS trial experiment in a tagged along mode in
the next step to further test and improve the station observation system.

3.2 Tianma13
The frequency band of Tianma13 is 3 GHz ∼ 18 GHz.
The efficiency is about 50 %. The equivalent temperature of the receiver is about 20 K. As shown in Fig. 2,
the left panel is a satellite map of the yard of Tianma
65-m antenna, the Tianma13 is at the right-lower corner.

4 Considerations of new VGOS stations
VLBI is hitherto the sole technique to determine CRF,
EOP and TRF simultaneously. VLBI is applied to determine the orientation and the referencing positions/ directions of the CRF as well as its densification.

VGOS-like Stations in China

15
Table 1: The aperture efficiency and SEFD of Sheshan13.

Frequency Elevation Efficiency SEFD
(GHz)
(◦ )
(%)
(Jy)
Broadband
4.45
56.99 52.26
2019
5.45
57.23 64.15
1522
6.45
57.48 42.74
1596
7.45
57.78 46.01
1501
8.45
58.03 53.71
1585
9.45
58.28 50.74
1669
10.45
58.53 54.71
1547
11.45
58.82 50.33
1706
Dual band X/Ka
7.15
45.19 61.78
1268
8.65
47.27 62.26
1171
9.15
45.86 61.36
1578
30.85
51.10 49.11
2892

Fig. 4: The system temperature of Sheshan13.
Mk4/DiFX fourfit 3.20 rev 2515

4C39_25.0PVC4F, No0150, ST
SESHAN13 - TIANMA13, fgroup B, pol XX
Fringe quality

7

SNR
252.2
Int time 27.677
Amp
12.408
Phase
0.0
PFD
0.0e+00
Delays (us)SBD -0.053395
MBD -0.000000
Fringe rate (Hz)0.021335
Ion TEC 0.000
Ref freq (MHz)6000.0000
AP (sec) 1.024
Exp.
v9709aExper # 16383
Yr:day 2019:190
Start 082701.02
Stop 082729.70
FRT 082715.00
Corr/FF/build
2019:195:135231
2019:196:083415
2019:143:075521
RA & Dec (J2000)
09h27m03.013936s+39˚02’20.851856"

Amp. and Phase vs. time for each freq., 7 segs, 4 APs / seg (4.10 sec / seg.), time ticks 5 sec

Validity

U
L

S T

All

3032.40 3064.40 3096.40 3224.40 3320.40 3384.40 3448.40 3480.40 5272.40 5304.40 5336.40 5464.40 5560.40 5624.40 5688.40 5720.40 6392.40 6424.40 6456.40 6584.40 6680.40 6744.40 6808.40 6840.40 10232.4010264.4010296.4010424.4010520.4010584.4010648.4010680.40Freq (MHz)Fig. 5: The broadband fringe between Sheshan13 and Tianma13.
0.0

-0.0

-0.1

-0.0

0.0

0.0

0.0

-0.0

-0.0

-0.0

-0.0

0.0

0.0

-0.0

-0.0

-0.0

0.0

-0.0

-0.0

0.0

-0.0

0.0

0.0

0.1

-0.0

0.1

0.0

0.1

0.0

-0.0

-0.0

0.0

Phase

13.1

12.0

8.9

16.9

10.5

8.8

1.4

2.1

12.0

15.9

15.5

17.9

13.7

8.9

16.0

13.2

18.2

17.6

18.8

20.2

20.0

19.1

16.8

19.0

7.8

7.6

7.9

5.5

8.2

8.2

7.4

7.4

Ampl.

0.0

12.4

2042.22042.5 2042.0 2041.7 2042.1 2041.9 2042.1 2040.0 2040.6 2042.7 2042.0 2042.7 2042.3 2043.1 2042.0 2041.9 2042.2 2042.4 2042.3 2042.3 2042.3 2042.1 2041.8 2041.7 2041.9 2042.3 2042.4 2042.6 2042.3 2042.1 2042.1 2042.2 2042.1 Sbd box
U/L

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

0/28

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

62.3

50.5

55.9

69.4

69.7

-48.7

54.2

57.6

52.0

54.8

74.2

53.8

47.5

36.2

47.6

53.6

43.1

52.5

53.9

PC X delays (ns)

-36:0

178:0

27:0

90:0

53:0

141:0

59:0

-104:0 -162:0 31:0

176:0

-147:0 -91:0

58:0-129:0 -84:0

28:0

-12:0

-67:0

45:0

PC phase

0:38

0:89

0:91

0:95

0:75

0:79

0:48

0:-137 0:16

0:33

0:55

0:38

0:-3

0:10

0:31

0:84

0:30

0:-174 0:-57

0:50

0:84

Manl PC

74

73

54

54

64

50

102

96

57

34

67

58

108

100

23

23

12

6

15

23

23

22

PC amp

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

-400

S

-19.2

-38.9

-97.9

-99.6

99.1

43.4

39.7

50.7

55.1

9.1

50.1

53.3

49.6

S:T

-41:0

146:0

-45:0

-177:0 -4:0

131:0

-62:0

52:0

47:0

-54:0

-90:0

-30:0

S:T

0:-6

0:77

0:165

0:107

0:80

0:63

0:149

0:146

0:49

0:-164 0:39

S

118

99

89

133

97

41

26

10

65

91

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

T

T
S

T

APs used
PC freqs

B00LX B01LX B02LX B03LX B04LX B05LX B06LX B07LX B08LX B09LX B10LX B11LX B12LX B13LX B14LX B15LX B16LX B17LX B18LX B19LX B20LX B21LX B22LX B23LX B24LX B25LX B26LX B27LX B28LX B29LX B30LX B31LX Chan ids
Tracks
B00LX B01LX B02LX B03LX B04LX B05LX B06LX B07LX B08LX B09LX B10LX B11LX B12LX B13LX B14LX B15LX B16LX B17LX B18LX B19LX B20LX B21LX B22LX B23LX B24LX B25LX B26LX B27LX B28LX B29LX B30LX B31LX Chan ids

VLBI determines the angular positioning precisions of
ERS up to milli-arcsecond (mas) or better. In TRF the
VLBI technique provides the referencing stations anddetermines the scale factor. The positioning precisionof long distance on the Earth is up to 1 ppb or better.
VLBI precisely determines all the EOP, improves thestudies of the EOP stimulation mechanism, Earth innerGroup delay (usec)(model)
Sband delay (usec)
Phase delay (usec)
Delay rate (us/s)
Total phase (deg)Tracks-4.30218965725E+02-4.30272360715E+02-4.30218965713E+02-8.93231448025E-04-285.9Apriori delay (usec)
Apriori clock (usec)
Apriori clockrate (us/s)
Apriori rate (us/s)
Apriori accel (us/s/s)-4.30218965715E+02-4.2249997E+02
0.0000000E+00-8.96787288025E-04
5.01469631540E-08

Resid mbdelay (usec)
Resid sbdelay (usec)
Resid phdelay (usec)
Resid rate (us/s)
Resid phase (deg)-9.27916E-09-5.33950E-02
2.25076E-09
3.55584E-06
0.0+/+/+/+/+/-

2.4E-07
6.8E-05
2.1E-07
1.3E-08
0.5

RMS
Theor.
Amplitude
12.408 +/- 0.049
Pcal mode: MULTITONE, MANUAL
PC period (AP’s) 5, 5
ph/seg (deg)
0.4
0.6
Search (64X1024) 11.548
Pcal rate: 0.000E+00, 0.000E+00 (us/s)
sb window (us)-1.000 1.000
amp/seg (%)
1.3
1.0
Interp.
0.000
Bits/sample: 2x2
SampCntNorm: disabled
mb window (us)-0.016 0.016
ph/frq (deg)
0.0
1.3
Inc. seg. avg.
12.383Sample rate(MSamp/s): 64
dr window (ns/s) -0.005 0.005
amp/frq (%)
42.4
2.2
Inc. frq. avg.
12.381
Data rate(Mb/s): 4096
nlags: 2048 t_cohere infinite ion window (TEC) 0.00 0.00
S: az 295.5 el 62.3 pa 96.6
T: az 295.5 el 62.4 pa 96.6
u,v (fr/asec) 0.462 0.282
simultaneous interpolator
Control file: cf_manual.txt Input file: /home/data/VGOS/v9709/1234_TT_0714/No0150//ST..0PVC4F Output file: Suppressed by test mode
Samplers: abcdefgh ijklmnop qrstuvwx yzABCDEF

structure modeling (Free core nutation) and geophysical models, in particular provides crucial and reliable
external constraints of geophysical models.
The selection of a new astrometric and geodetic
VLBI observation site requires comprehensive considerations about the radio interference background, climate characteristics, historical archive of disastrous
weather records, geographical location, as well as convenience in transportation, water and electricity supply, electronic communication and so on. Some otheraspects are also meaningful to be mentioned concerning for instance the geometric shielding of the antenna,
Ka-band observation and supporting to deep space exploration.
Fig. 6 shows the correlation between the station
vertical coordinate and the excess zenith delay of atmosphere (Wen et al., 2017) from covariance analysis,
where σU , σZd and RUZd represent respectively the uncertainty of the vertical coordinate, that of the excess
zenith delay and the correlation coefficient. It is shownthat the coefficient is larger than 0.80 at elevation 20◦ ,and is still larger than 0.55 even at elevation 7◦ . Therefore in the selection of a new site the significant geometric shielding should be avoided in order to get precise vertical coordinate determination of the station.
Compared to X-band, the advantages of VLBI
observations at Ka-band include more compact extragalactic sources, relatively smaller effect of coreshift, as well as helpful to improve the precision in therealization of radio celestial reference frame and in
the linkage to the quasi-inertia optical frame of Gaia
project (Li et al., 2017). Advantages in terms of deep

16

Li et al.

devoting to the development of the next generation radio telescopes for astrometry and geodesy, the VGOSlike stations. As the continuation of technical practiceand the accumulation of implementation experience wewill have more new VLBI stations in the near future.
We are also seeking opportunities to develop some international VGOS-like stations by cooperation. Someconsiderations on the development of VGOS stations
are presented for criticism and reference.

References

Fig. 6: Correlation between the station vertical coordinate andthe excess zenith delay of atmosphere.

space exploration are high in telemetry data rate, highin VLBI tracking precision, and helpful to mitigate
detrimental effects of ionosphere and solar plasmaon the observed time delay. Disadvantages include
relatively weak extragalactic sources, high precision
requirement of reflector and antenna pointing, andsusceptible to atmospheric absorption and emission
effects. But the loss in system sensitivity due to thesefactors could be mostly compensated by the rapid
development in high data rate sampling and recording
techniques. Therefore the Ka-band VLBI observations
are strongly recommended in the development of new
VGOS stations.

5 Concluding remarks
Since the development of the experimental system ofradio telescope in China in 1970s, the CVN has been
greatly contributed to studies of astrophysics, astrometry and geodesy for more than forty years, and also
to the CELP and other deep space exploration projects
of China for more than ten years. Various institutions/ institutes of China through various projects are now

Heki K (1995) Movement of the Shanghai station: Implication
for the tectonic of eastern Asia. J Commun Res Lab, 42(1):
65–72
Hong X (2007) VLBI techniques and application in the Chang’E
lunar orbiter (in Chinese). Chinese Journal of Nature, 29(5):297–299
Li J, Huang F, Sun Z (2017) Analysis of the advantages anddisadvantages of astrometric and geodetic VLBI observation
at Ka-band. Geomatics and Information Science of Wuhan
University, 42(2): 257–262
Li J, Wang G (2001) The relative motion of Shanghai VLBI
station to the stable part of Eurasia plate. Annals of Shanghai
Observatory Academia Sinica, (22): 57–62
Li J, Wei E, Sun Z, et al. (2010) Discussion on future configuration design of Chinese astrometric and geodetic VLBI network. Geomatics and Information Science of Wuhan University, 35(6): 670–673
Li J, Xiong F, Yu C, et al. (2014) Precise determination of thereference point coordinates of Shanghai Tianma 65-m radio
telescope. Chinese Science Bulletin, 59 (21): 2558–2567
Petrachenko B, Niell A, Behrend D, et al. (2009) Design aspectsof the VLBI2010 system. In: D. Behrend, K. Baver (eds.),
IVS 2009 Annual Report, NASA/TP-2009-214183, 13–67
Wan T, Qian Z, Wu L, et al. (1983) Summary results of the
Shanghai-Effelsberg VLBI experiment. Chinese Astronomy
and Astrophysics, 7(2): 145–150
Wan T, Wu H, Qian Z, et al. (1987) The first joint SinoJapanese experiment of very-long-baseline interferometry(VLBI). Science in China Ser A, XXX(3): 307–316
Wen B, Li J, Sun Z, et al. (2017) Discussion about the shieldingof topographical features surrounding the astrometric andgeodetic VLBI station. Geomatics Science and Engineering, 37(1): 21–25

Measuring Focal Length Variations of VGOS Telescopes
Using Unmanned Aerial Systems
M. Lösler, C. Eschelbach, R. Haas, A. Greiwe

Abstract VLBI radio telescopes are large technicalfacilities whose structures are affected by several
deformation patterns. In particular, temperature- andgravity-dependent deformations bias the estimatedglobal telescope position and, therefore, if uncorrected,
deteriorate the geodetic results that can be derived fromthe geodetic VLBI analysis. The rigidity of a telescope
structure under varying acting forces is restricted byits structural properties. Large conventional radio
telescopes are more affected by deformation effects
than the new compact-designed VGOS antennas. The
design document for the next generation VLBI system(today called VGOS) states <300 µm as requirement
for the path length stability. A traceable metrologicalsystem that can be used to check this stability levelmust be at least three times better than the requirements. Close range photogrammetric methods fulfil
these accuracy requirements but usually need a craneduring the survey of a telescope. To avoid the latter,an unmanned aerial system was used for the firsttime to evaluate the possible deformation of the mainreflector surface of the north-eastern of the Onsala
twin telescopes (ONSA13NE). The focal length of thering-focus paraboloid was derived in several elevation

angles to study the gravitational deformation effects
on the main reflector of this VGOS antenna.

Keywords VGOS · Ring-focus paraboloid · Antenna
deformation · Focal length · Unmanned aircraft system

1 Introduction

Ansgar Greiwe
University of Applied Sciences Bochum, Lennershofstraße 140,
DE-44801 Bochum, Germany

The backbone of the next generation geodetic VLBI
system will be formed by a new designed type of radio
telescopes. These new radio telescopes, often refereed
to as VGOS1 radio telescopes, are of a more compact
design and are able to move faster than conventional radio telescopes. One of the most important advantagesof the compact design is the stability of the telescope
structure against acting forces. However, radio telescopes are large technical facilities and the rigidity is
restricted by structural properties. Known deformation
patterns of conventional radio telescopes like thermal
expansions (e.g. Haas et al., 1999), seasonal variations(e.g. Mähler et al., 2018) or gravitational sags (e.g.
Bergstrand et al., 2018) can be fully transferred to the
VGOS generation of radio telescopes, but have partly
smaller amplitudes. Moreover, most of the VGOS radio telescopes make use of an improved main reflector
design, i.e., the ring-focus paraboloid. Hence, measurement methods and mathematical models, which weresuitable for conventional radio telescope, are not necessarily applicable for VGOS.
Thermal and seasonal variations of VGOS antennas
have been investigated and modeled (e.g. Lösler et al.,2013; Mähler et al., 2018). However, gravitational de-(Correspondence: michael.loesler@fb1.fra-uas.de)

1 VLBI Global Observing System

Michael Lösler · Cornelia Eschelbach
Frankfurt University of Applied Sciences, Laboratory for Industrial Metrology, Nibelungenplatz 1, DE-60318 Frankfurt am
Main, Germany
Rüdiger Haas
Chalmers University of Technology, Onsala Space Observatory,
SE-439 92 Onsala, Sweden

17

18

Lösler et al.

formations of the main reflector are not studied in detail so far. In this investigation, the focal length variations of ONSA13NE, the north-eastern of the Onsala
twin telescopes, is derived to analyse the deformation
behavior of a VGOS antenna. Moreover, an unmanned
aerial system (UAS) is used to observe the main reflector in several elevation angles, for the first time.
Fig. 1: Differences in spectral information acquirements be-

tween Foveon based sensorS (left) and color filter arrays like
Bayer pattern (right) (Verhoeven, 2010).

2 UAS-based observation strategy
Close range photogrammetry has a long history in radio telescope surveying, dating back to the early 1960s(e.g. Findlay, 1964). Usually, photogrammetric methods are used to adjust the panels of the main reflector(e.g. Süß et al., 2012). On the one hand, advantages
are the achievable uncertainties of 100 µm for discrete signaled markers and no heavy equipment has tobe mounted onto the telescope which may cause further deformations. On the other hand, a large crane isneeded to retrieve a block configuration with suitable
camera positions in several elevation angles of the telescope.
Since recent years, unmanned aerial systems (UAS)
are well-established as sensor platform for small format close range aerial photogrammetry. The unmanned
aerial vehicle (drone) is equipped with several navigation sensors, e.g. GNSS and IMU, and remote controlled by a ground-station. Usually, the waypoints ofthe flight path as well as the trigger points for the camera are scheduled by a flight plan. Due to practical reasons, in this project the camera was controlled remotely
by the pilot via video screen.
The equations of the central projection, whichtransforms three dimensional object coordinates( XP YP ZP )T to corresponding planar image coordinates ( x y )T , are given by
(
(

)
)

(
(

)
)

(
(

) +∆x ,
)

(1a)

(
(

)
)

(
(

)
)

(
(

) +∆y .
)(1b)

XP −X0 +r21 YP −Y0 +r31 ZP −Z0
r13 XP −X0 +r23 YP −Y0 +r33 ZP −Z0rx =x0 −c 11

XP −X0 +r22 YP −Y0 +r32 ZP −Z0
r13 XP −X0 +r23 YP −Y0 +r33 ZP −Z0ry =y0 −c 12Here, the principal distance c, the principal point x0 ,y0 and the distortion effect parameters ∆x , ∆y , which
compensate for the radial-symmetric lens distortionand the decentring distortion, are known as interior orientation, which are usually constant for all images of aphotogrammetric bundle. The parameters of the exterior orientation refer to the image position and orientation w.r.t. the global reference frame and are givenby  X0  
P0 =  Y0  ,
 
Z0



 r11 r12 r13 
R =  r21 r22 r23  ,
r31 r32 r33

respectively (cf. Luhmann, 2018, Ch. 4.2.1).
The weight of the camera restricts the operatingtime of the UAS. For that reason, a lightweight 380 g
consumer camera Sigma DP3 Merrill was used instead of a heavy high-precision photogrammetric camera. This yields in a flight time of about 25 min. Dueto the fact that consumer cameras are not geometrically stabilized, the parameters of the interior orientation were calibrated in-situ during the bundle adjustment for each measurement campaign (e.g. Luhmann,
2018, Ch. 4.4.2).
The image sensor of the camera based on the
Foveon chip and captures full color informationfor each pixel (e.g. Greiwe and Gehrke, 2013). For
comparison, the elements of color filter arrays like
Bayer pattern are only sensitive for one waveband
and the full color is obtained by interpolations (e.g.
Verhoeven, 2010). Figure 1 depicts the differencesin acquired spectral information between a Foveon
based sensor and a color filter array. Full true color
information increases the micro-contrast and leads tobetter image measurements e.g. edge detection during
the analysis process. The main reflector surface of
ONSA13NE2 , the north-eastern of the Onsala twin
telescopes, was equipped by 72 discrete 12-bit coded
markers. Additionally, four markers were attached
2 https://youtu.be/sNnHvBaQ3 w

Focal Length Variations of VGOS Telescopes

19

symmetry of the main reflector, cf. Table 1. Figure 3
depicts the established flight plan for elevation angle
30°.
Instead of using a configuration where the camera
orientation is aligned to the axis of symmetry of themain reflector, the diametrical direction of the main reflector was pointed for each taken image. About 150
suitable images were taken per campaign and analysedby the bundle adjustment software package AICON 3D
Studio. The software extracts coded markers as well as
natural circular targets at the telescope e.g. screws automatically. Thus, more than 500 points are used during the adjustment process per campaign. The uncertainties of the coded markers are between 80 µm and120 µm w.r.t. the global datum. A detailed description
is given by Lösler et al. (2019).

3 Focal length variations

several coded markers, scale-bars and coordinate cross during
the UAS-based photogrammetric survey of the main reflector
surface.

at the sub-reflector together with a coordinate cross,which approximately defines the datum of the resulting
point clouds by six markers. To transfer the point cloud
into a metric system six carbon fiber scale-bars wereattached at the sub-reflector, at the strut elements
and at the rim of the dish. Figure 2 depicts the
prepared main reflector surface of the ONSA13NE
during a UAS-based measurement campaign, using a
HP-TS960 (HEXAPILOTS).
To obtain a possible deformation pattern of themain reflector, measurement campaigns were carriedout redundantly from elevation 0° up to 90° using a
step-size of 10° as well as one time in 34°. The flightplan for each elevation angle consists of two flight lines
and two concentric spatial circles around the axis of

As most of the new VGOS radio telescopes, the mainreflectors of the Onsala twin telescopes are designed as
rotational symmetric ring-focus paraboloids (e.g. Pantaleev et al., 2017). A ring-focus paraboloid results bycombining two quadric surfaces, i.e. a paraboloid anda cylinder. A closed mathematical model of a doubleelliptic ring-focus paraboloid was recently derived byLösler et al. (2017, 2018a,b, 2019) and readsa21 (xi − ri n x,i )2 + a22 (yi − ri ny,i )2 = zi .

30
25
20
15
10
Ring-focus
Traverse
Circle5

Table 1: Parameter of the flight plan that is used for each mea-

surement campaign. The distances are related to the apex of themain reflector surface.
Type
Traverse (m)Circle (m)Distance
14
14
19
Radius
–6.5 11.5(2)35Height in m

Fig. 2: The VGOS radio telescope ONSA13NE equipped with

33314909
33314899

UTM-East in m

33314889

636540363654106365417UTM-North in m

Fig. 3: Established flight plan for elevation angle 30° that con-sists of two traverses and two circles. The main reflector surface
is plotted in the background.

20

Lösler et al.

Table 2: Estimated RMS w.r.t. different survey elevations .


0° 10° 20° 30° 34° 40° 50° 60° 70° 80° 90°
RMS 204 187 200 167 169 192 182 173 178 221 282
in µm 190 194 166 147 – 154 155 162 167 227 292

The paraboloid parameter a yields the focal length
via F = 4a12 .
Figure 4 depicts the estimated focal lengths of the
21 measurement campaigns by red dots. Red error-bars
indicate the related uncertainties (2σ). The focal length
varies in a range of ±1.1 mm and depends on the elevation angle. The maximum occurs at 90°, which confirms the assumption that the main reflector becomesflatter in higher elevation positions (cf. Lösler et al.,2019).
To predict the variations by a suitable function, acommon cosine function was adapted, i.e.,
F() = 3.7017 m − 2.3 mm cos .

(3)

3.704

Focal length F in m

Here, a1 and a2 are the parameters of the elliptic
paraboloid and ( xi yi zi )T are the coordinates of
the ith point lying on the paraboloid surface. The
point-dependent cylinder parameter ri = f (b1 , b2 , φ)results from the inverse semi-major and the inverse
semi-minor axes b1 and b2 , respectively, and thecylinder orientation φ. The normalized normal vector
perpendicular to the cylinder axis is denoted by ni . In
case of a rotational symmetric ring-focus paraboloid,
the restrictions a1 = a2 and b1 = b2 hold (cf. Lösler
et al., 2018a,b). By applying a rotation sequence anda translation, the canonical form is transformed to anarbitrary position in space.
The estimated point sets of each bundle adjustment
were corrected for thermal expansions. The parametersof the ring-focus paraboloid were derived by Eq. 2 using a proper errors-in-variables (EIV) solver. For rigorous uncertainties propagation, the dispersion of theestimated point sets was introduced to the EIV to define the a-priori stochastic model of the observations.
Table 2 summarizes the campaign-wise estimatedoverall RMS values. The panels were adjusted at elevation 34°, thus, smallest deviations can be expected forelevation angles close to 34°. This assumption is confirmed by the estimated RMS values, because larger
values can be found close to 0° and 90°, whereas smallest values are given from 30° to 50°.

3.703
3.702
3.701
3.700
3.699
0

10

20

30

40

50

60

70

80

90

Elevation in °Fig. 4: The estimated focal length of the 21 measurement cam-paigns with uncertainties (2σ) are illustrated by red dots. The
derived prediction function and the related confidence interval(2σ) are plotted in black and grey, respectively.

The resulting prediction function is plotted as blackline. The grey colored band indicates the related 2σ
confidence.
For comparison, the variations of the focal length
are 10-times smaller than reported for conventional radio telescopes (e.g. Sarti et al., 2009; Nothnagel et al.,2013; Bergstrand et al., 2018). The compact-design aswell as technological improvements result in a higher
rigidity and damped deformations and correspond to
the theoretical intention of the VGOS-specifications(Petrachenko et al., 2009).

4 Conclusions
For the fist time, elevation-dependent gravitational deformations of the main reflector of a VGOS-specified
radio telescope were studied in detail at the OnsalaSpace Observatory. The focal length of the northeastern of the Onsala twin telescopes (ONSA13NE)
varies by about ±1 mm and can be predicted by acosine function.
For this purpose, photogrammetric methods wereused to observe the radio telescope in several elevation
angles. Instead of using a large crane for data recording, an unmanned aircraft system (UAS) carried out thesurveying campaigns. To our knowledge, this was thefirst time that an UAS is used in radio telescope surveying. The uncertainties of a discrete measured point
was about 100 µm and fulfilled the requirements to
be at least three times better than the expected variations. Summarized, for free-standing radio telescopes,
the UAS provides a promising and practicable surveying method. Neither a crane is required nor additional
heavy equipment has to be mounted.

Focal Length Variations of VGOS Telescopes

Acknowledgements We thank Lars Wennerbäck and Christer
Hermansson for mounting and dismounting the coded markers
and the scale-bars at the radio telescope.
This research project is part of the JRP 18SIB01 ”Largescale dimensional measurements for geodesy” (GeoMetre) andhas received funding from the EMPIR programme co-financedby the Participating States and from the European Union’s Horizon 2020 research and innovation programme.

References
Bergstrand S, M. Herbertsson M, Rieck C, et al. (2018) A gravitational telescope deformation model for geodetic VLBI.
J Geod, 93(5), 669–680, doi:10.1007/s00190-018-1188-1
Findlay J W (1964) Operating Experience at the National
Radio Astronomy Observatory. Annals of the New York
Academy of Sciences, 116(1), 25–40, doi:10.1111/j.17496632.1964.tb33937.x
Greiwe A, Gehrke R (2013) Foveon Chip oder Bayer Pattern- geeignete Sensoren zur Aerophotogrammetrie mit UAS.
In: T. Luhmann, C. Schumacher (eds.): Photogrammetrie Laserscanning - Optische 3D-Messtechnik: Beiträge der 12.
Oldenburger 3D-Tage 2013, Wichmann, Offenbach, 334–
343, ISBN: 978-3879075287
Haas R, Nothnagel A, Schuh H, et al. (1996) Explanatory supplement to the section ’Antenna Deformation’ of the IERS Conventions (1996). In: H. Schuh (Eds.): Explanatory supplement to the IERS conventions (1996), Deutsches Geodätisches Forschungsinstitut (DGFI), München, 71, 26–29
Lösler M, Neidhardt A, Mähler S (2013) Impact of Different
Observation Strategies on Reference Point Determination– Evaluations from a Campaign at the Geodetic Observatory Wettzell. In: N. Zubko and M. Poutanen (eds.): Proc.
21st EVGA Working Meeting, 255–260, ISBN: 978-951711-296-3
Lösler M, Eschelbach C, Haas R (2017) Unified Model for Surface Fitting of Radio Telescope Reflectors. In: R. Haas,
G. Elgered (eds.): Proc. 23rd EVGA Working Meeting, 29–
34, ISBN: 978-9188041098
Lösler M, Eschelbach C, Haas R (2018a) Applying Bootstrapping in the Framework of Uncertainty Estimation exem-

21

plified by Surface Analysis. zfv – Zeitschrift für Geodäsie,
Geoinformatik und Landmanagement, 140(4), 224–232,
doi:10.12902/zfv-0214-2018Lösler M, Eschelbach C, Haas R (2018b) Zur Modellierung eines
Ring-Focus-Paraboloids. In: T. Luhmann, C. Schumacher(eds.): Photogrammetrie – Laserscanning – Optische 3DMesstechnik: Beiträge der 17. Oldenburger 3D-Tage 2018,
Wichmann, Offenbach, 222–234, ISBN: 978-3-87907-643-7
Lösler M, Haas R, Eschelbach C, et al. (2019) Gravitational
Deformation of Ring-Focus Antennas for VGOS – First Investigations at the Onsala Twin Telescopes Project. J Geod,
doi:10.1007/s00190-019-01302-5
Luhmann T (2018) Nahbereichsphotogrammetrie - Grundlagen,
Methoden und Anwendungen, Wichmann, Berlin, 4th edn,
ISBN: 978-3879074792
Mähler S, Klügel T, Lösler M, et al. (2018) Permanent Reference Point Monitoring of the TWIN Radio Telescopes at theGeodetic Observatory Wettzell. avn – Allgemeine Vermessungsnachrichten, 125(7), 210–219
Nothnagel A, Eichborn M, Holst C (2013) Improvment of focal length results of Effelsberg 100 m radio telescope. In:
N. Zubko and M. Poutanen (eds.): Proc. 21st EVGA Working Meeting, 55–59, ISBN: 978-951-711-296-3
Pantaleev M, Haas R, Billade B, et al. (2017) Onsala Space
Observatory – IVS Technology Development Center Activities during 2015-2016. In: K. D. Baver, D. Behrend,and K.L . Armstrong (eds.): International VLBI Service forGeodesy and Astrometry 2015+2016 Biennial Report, 301–
305, NASA/TP-2017-219021
Petrachenko B, Niell A, Behrend D, et al. (2009) Design aspectsof the VLBI2010 system. NASA/TM-2009-214180
Sarti P, Vittuari L, Abbondanza C (2009) Laser Scanner andTerrestrial Surveying Applied to Gravitational Deformation
Monitoring of Large VLBI Telescopes’ Primary Reflector. J Geod, 135(4), 136–148, doi:10.1061/(ASCE)SU.19435428.0000008
Süß M, Koch D, Paluszek H (2012)
The Sardinia Radio Telescope (SRT) optical alignment. Proceedings ofGround-based and Airborne Telescopes IV, 8444, 84442G1–84442G-16
Verhoeven G J J (2010) It’s All about the Format – Unleashing
the Power of RAW Aerial Photography. Int. J. Remote Sens.,
31(8), 2009–2042, doi:10.1080/01431160902929271

Instrumentation Developments for VGOS at IGN Yebes
Observatory
J. A. López Pérez, P. de Vicente, J. A. López Fernández, F. Tercero Martı́nez, J. D. Gallego,
J. M. Serna Puente, I. López Fernández, M. Dı́ez González, I. Malo Gómez, C. Albo Castaño,
L. Barbas Calvo, O. Garcı́a Pérez, J. González Garcı́a, B. Vaquero Jiménez, M. Patino Esteban,
P. Garcı́a Carreño, F. J. Beltrán Martı́nez, M. Bautista Durán, J. López Ramasco, R. Amils Samalot,
G. Gómez Molina, A. Baldominos Delgado

Abstract IGN Yebes Observatory keeps on developing the required instrumentation for its RAEGE network of VGOS radio telescopes, together with broadband receivers for other institutes like NMA and FGI
which are finishing their VGOS antennas. These developments include new VGOS receivers, low noise amplifiers and hybrid circuits, feed optimization, phasecal
and noisecal units, cryogenic cooling control units, RFI
monitorization and telescope control.

Keywords VGOS · RAEGE · Receiver · Amplifier ·Feed · RFI · Geodesy

The observatory also operates two radio telescopes,
13.2 m and 40 m in diameter, respectively (see Fig. 1);
the first one runs regularly VGOS observations and thesecond one, legacy IVS observations since 2008. Two
GNSS receivers are managed too: one integrated in theinternational network and a second one in the Spanish
national one. It also runs two gravimeters, an absoluteand a relative superconductor one.
Funding has been approved for the installation of
an SLR (Satellite Laser Ranging) station in the next 5
years which would transform Yebes Observatory into a
GGOS core station.

2 RAEGE project1 Introduction
The Yebes Observatory of the Spanish Dirección General del Instituto Geográfico Nacional (IGN) keeps on
developing the required instrumentation for its RAEGE(Red Atlántica de Estaciones Geodinámicas y Espaciales) network of VGOS radio telescopes in Yebes,
Santa Maria, Gran Canaria and Flores. In addition, it
is developing instrumentation for other institutes, like
NMA, FGI or BKG. These developments include new
VGOS receivers, low-noise amplifiers and hybrid couplers, feeds, phasecal and noisecal units, vacuum andcryo-cooling control units, telescope control softwareand local-tie measurements. Finally, RFI monitoring is
performed, too.
José Antonio López Pérez et al.
Observatory of Yebes - Instituto Geográfico Nacional
Cerro de la Palera S/N Yebes, Spain(Correspondence: jalfernandez@fomento.es)

The Spanish-Portuguese collaboration in RAEGE
project is still active and the Santa Maria station

Fig. 1: Yebes Observatory telescopes. From left to right: ESSCO

13.7 m (radome), ARIES 40 m and VGOS 13.2 m.

22

VGOS at IGN Yebes

has resumed VLBI observations with a simultaneoustri-band (S/X/Ka) receiver.
The civil works for the VGOS telescope in Gran
Canaria island have been delayed due to administrativeand environmental authorizations for the selected site
(Artenara). It is expected to start with these works inlate 2019.
Similarly, the VGOS telescope in Flores island(Azores) is delayed too. It it expected to perform thecall for tenders for the construction of this telescope in
2020.

23

Fig. 2: Schematics of the VGOS broad band receiver for NMA

and FGI.

3 Broad-band receivers
Yebes Observatory is responsible for the design andconstruction of three cryogenic VGOS broadband receivers: two for the Norwegian Mapping Authority(NMA) and one for the Finish Geospatial ResearchInstitute (FGI). A fourth one is in progress for Santa
Maria RAEGE/VGOS station.
These broadband receivers are cooled using a twostage cryostat (15 and 50 K) and operate between 2
and 14 GHz. They have cryogenic low noise amplifiers
designed and built at Yebes laboratories and deliver a
receiver temperature below 25 K along the whole bandin a free RFI environment. They provide two linear orthogonal polarizations simultaneously.
Two of them will be delivered by the second half of2019, one to NMA and one to FGI, respectively.
Fig. 2 shows the receiver block diagram in which
we can see its different modules. It follows the approach shown in Garcı́a Carreño et al. (2016) withsome upgrades. After the cryostat, the signal is split
in two sub-bands: 2.1 − 5.6 GHz and 3.6 − 11.6 GHz
following Haystacks’s approach to avoid the saturationof the optical fiber amplifiers from strong RFI signals
in the lower part of the band. The signals once amplified, filtered and transported through optical fiber links
to the backends room, are directed towards two identical DBBC3 RF interface modules designed and built at
Yebes. These modules split the signals from both polarizations into four frequency sub-bands ready to be
injected into the DBBC3. The filtering and conditioning module for the DBBC3 does not use tuneable LOs
and in case that the observing bands change they canbe adapted by replacing the pass band filters by new
ones.

Fig. 3: Receiver temperature for the FGI broadband receiveralong the band.

Fig. 3 shows the receiver temperature measured inboth linear polarizations along the band. The peaks at
low frequencies are mainly due to RFI associated to
WiFi, UMTS, Bluetooth, WiMax and other sources ofnoise. They are also caused by mismatching between
QRFH feed and LNAs.
The receivers use a cryogenics and vacuum control system which has been overhauled from a previous
version used in the Yebes VGOS receiver. This new
version has a remote ethernet connection to the Local
Area Network that allows remote monitoring and control of both pumps (rotatory and turbomolecular), thecryogenic temperature, the vacuum sensors, the electrovalve, and the heat resistors and regenerators. This
remote monitoring and control eases the operation of
the receiver, adds stability and provides a complete
time log of the cryogenics. It is integrated in the control
system of the telescope and can be used by third party
software.

24

López Pérez et al.

4 Tri-band receiver for Ny-Ålesund
The NMA runs two twin VGOS radio telescopes at
Ny-Ålesund station which were inaugurated during thelast IVS General Meeting in June 2018. In order to test
these radiotelescopes, NMA borrowed from Yebes Observatory one tri-band receiver which simultaneously
works in the bands 2.2 − 2.7 GHz, 7.5 − 9 GHz and
28 − 32 GHz. The receiver was mounted first in one
antenna and then in the second one to test the telescopes and determine the pointing and focusing model.
The SEFD and the efficiency at X-band were estimated.
Both telescopes were using the Yebes control softwareand the Yebes pipeline and reduction software. Receiver temperatures are below 30 K at S, X and Ka bandin all cases.
Yebes staff has assisted NMA in the installation andoperation of this receiver.
It has to be mentioned that the X-band LNAs werebroken due to high RFI from radars emitted by ships
coming in the Ny-Ålesund fjord. They were replaced
and now the pointing to the fjord is avoided.

5 QFRH revisited
Yebes Observatory has worked in the optimization of
the QFRH design from JPL used in the VGOS radio
telescopes. The Yebes design resembles the original
design but has slightly changed the profile and the connectors (coaxial ones). The antenna works between 2.3
and 14 GHz in dual linear polarization. The drawings
allow to manufacture it easily. The efficiency is slightly
better than the original design, above 0.55 along thewhole band, but the reflection is slightly worse (seeFig. 4.

6 Linear to circular polarization: hybrids
and software
One of the main drawbacks of broadband receivers isthe need to use linear polarization. This has prevented
an easy simultaneous operation with the IVS legacy
observations which only use Left Circular Polarization(LCP). The usage of linear polarization generates new

Fig. 4: Efficiency by the QFRH along the frequency band.

problems to be taken into account like variable polarization coming from the paralactic angle which differs
at the different radio telescopes on the Earth. Sources
may be totally or partially polarized and since their paralactic angle changes with time it is necessary to observe in both polarizations to recover the whole signal.
Furthermore, instrumental effects should also be taken
into account. The conversion from linear to circular polarization can be done by either software or hardware.
Yebes Observatory has developed a solution basedon cryogenic 3 dB/90-deg multi-octave stripline hybrids which can be used to obtain both circular polarization signals from linear polarization ones. The usage of such devices at cryogenic temperatures (15 K)
only increases 1.5 K in average the noise temperatureof the LNAs. This solution guarantees cross polarization below 25 dB, an axial ratio below 1 dB, an amplitude unbalance below 0.9 dB and a phase unbalancelower than 3 degrees. To achieve such specifications thelength of the lines has to be controlled with great accuracy but this is achievable using special connectors.
Fig. 5 shows the hybrids performance along the frequency band. This solution has not been implemented
on a geodetic VLBI receiver yet, but BRAND projectfrom Radionet, is considering it as a first option.
The alternative approach to convert linear to circular polarization is by software using PolConvert software by Ivan Martı́-Vidal. This task is part of the effort
started by the EU-VGOS project which aims to create

VGOS at IGN Yebesa pipeline that performs the correlation, polarization
conversion, instrumental polarization calibration andfringe fitting along the whole band to estimate the dispersive effects of the ionosphere. The goal is to obtainthe final observable: the broadband delay for each scanand baseline from which the length of the baselines is
estimated. EU-VGOS observes regularly with the European antennas from Onsala, Wettzell and Yebes totest this pipeline currently under development.

25

One for the 2 − 14 GHz band and another for the 1.5 −15 GHz band (BRAND receiver).
The behaviour of both amplifiers is shown in Fig. 6.

7 Ultra low noise wide band amplifiers
Yebes Observatory has developed two kind of low
noise cryogenic ultra wide band amplifiers in the band
between 2 and 14 GHz. The first option is a compact, light single-ended amplifier which is usable in amuch larger band, between 0.5 and 18 GHz. The average noise temperature is 6.1 K, the gain 33.9 dB, withan input IRL of −1.5 dB and an ORL of −16.9 dB.
The power consumption is 36 mW. This amplifier hasa large input reflection and an alternative solution wasinvestigated using a balanced amplifier.
The balanced amplifier uses 3 dB/90-deg hybrids
and the results are excellent. The penalty for using thehybdrids is very low. The noise temperature increases
only 1.5 K in average, up to 7.6 K, the gain is 33.8 dB
but the IRL drops to −21 dB and the ORL to −23 dB.
Two versions of balanced LNA have been developed.

Fig. 6: Noise temperature and gain of single ended and balanced

amplifiers.

8 Phase Cal developments

Fig. 5: Hybrid performance: transmission, reflection, amplitude

error and phase error, along the frequency band.

The phase cal system for VLBI is composed of two
subsystems: the antenna unit and the cable delay measurement system which estimates the variable delayin the signal caused by the cables between the receiver and the VLBI backends. This system devised by
A. Rogers is very powerful and it is in use at the IVS
radio telescopes.
We have optimized the antenna unit system by providing extra features. The noise and phase unit at Yebes
is installed at the receiver trolley, very close to the cryostat. It uses short semirigid coaxial cables to decrease
the variability caused by temperature variations in the26receiver cabin. The system generates pulses 10 MHz
apart and works between 2 and 14 GHz. The pulse generator is based on Hittite ultrafast logic gates, a similar
approach as in Haystack. The noise cal can be switched
at 80 Hz rate. The whole unit is shielded and it is temperature stabilized using a Peltier cooler and passive
insulation. The control and monitoring of the unit isdone with a Rapsberri Pi using Python scripts. Yebeslabs have built 9 units for BKG, AGGO, NMA, FGI
and Yebes and is integrating this system in the VGOS
receivers in construction for NMA and FGI.
The Cable Delay Measurement System (CDMS) isbased on the legacy design but it has been adapted ina single PCB to simplify its usage. A new CDMS isbeing developed and is still under tests; it does not require a frequency counter. The system compares the
5 MHz reference from the generator module with the
5 MHz signal coming from the antenna unit installed in
the receiver trolley. Both signals are phase compared ina phase detector, whose DC output is read by a 24-bit
ADC. The achieved RMS is < 5 ps, which corresponds
to < 0.003 degrees in phase. This system yields higher
sensitivity and lower phase noise. It is currently undertests and will be extended to other telescopes once it isvalidated.

9 RFI measurements
After several test to avoid a Tsys increase due to
RFI, the configuration shown in Fig. 7 was adopted.
A 3 GHz high-pass filter was installed at the dewar’s output. In addition, a PIN diode power limiter(+6 dBm) was installed at each optic fiber link input,
in order to protect them from damage due to strong
RFI which is present and could enter the receiverduring antenna maintenance at 0 deg elevation. With
this configuration, we managed to reduce Tsys from70 K down to 50 K.
In addition, a line of research on high temperature
superconducting filters (HTS) has been started at Yebeslabs (Huang et al., 2018).The initial project was a sharp
HTS filter for the legacy S-band, which is the worst one
in terms of RFI. The specifications for this filter werevery selective in order to reject high power radiolinks
close to this band.
After this, the simulation of an HTS filter for VGOS
is underway with promising results. The current con-López Pérez et al.

Fig. 7: Yebes VGOS receiver configuration.

figuration considered for VGOS is a band-pass filter(2−14 GHz) with one notch at a pre-defined frequency.
Finally, it has to be mentioned that a new RFI monitoring station has started operations on the roof of thelaboratory building. It allows the monitorization of RFI
from 1 to 40 GHz.

10 Conclusions and outlook
Two large and ambitious goals for Yebes Observatory
are planned for the next four years using European
funds from regional development. The first one is theconstruction of a future Satellite Laser Ranging station
at Yebes. In the next months we will make a study of
the requirements for the telescope and ancillary equipment and the software. Once this is decided, the acquisition of the equipment will take place and later thebuilding that hosts the telescope will be built.
The second goal consists in the extension of the current building of laboratories and workshops. The newbuilding, whose civil works will start shortly, will hostseveral laboratories, including a clean room and workshops to host precision milling machines and lathes aswell as metrology equipment.

References
Garcı́a Carreño P, Garcia Alvaro S, López Peréz J A, et al.
(2016) Geodetic VLBI ultra low noise broad-band receiverfor 13 meter VGOS radiotelescopes. In: Proc. 11th European Microwave Integrated Circuits Conference, 476–479.
doi:10.1109/EuMIC.2016.7777595
Huang F., Bolli P., Cresci L., et al. (2018) Superconducting
spiral bandpass filter designed by a pseudo-Fourier technique. IET Microw. Antennas Propag., 12(8), 1293–1301,
doi:10.1049/iet-map.2017.0940

DBBC3 Towards the BRAND EVN Receiver
G. Tuccari, W. Alef, S. Dornbusch, R. Haas, K.-Å Johansson, L. La Porta, H. Rottmann, A. L. Roy,J. Wagner, M. Wunderlich

Abstract The DBBC3 is a flexible VLBI backend andenvironment that supports a wide range of observational needs via a suite of FPGA firmware types. The
hardware can sample up to eight 4 GHz-wide baseband
signals and convert to digital streams over multiple
10GE links on fibre. The development team has an ongoing development programme that has enhanced existing modes and introduced new desired modes as user
requirements evolve. Three different firmware types forobserving have been implemented which will be briefly
summarised: Direct Sampling Conversion (DSC), arbitrary selection of bands (OCT), Digital Down Conversion (DDC). These modes cover all the requirementsof astronomical, VGOS and legacy geodetic VLBI of
the present, but also of the near future. At the sametime the DBBC3 is an important platform for additional new modes to be implemented for the BRAND
receiver. This paper describes the use of the DBBC3
for the receiver development, pointing out which element in the current DBBC3 structure will be part ofthe BRAND receiver in order to simplify its introduc-

Gino Tuccari
INAF Istituto di Radioastronomia, Sezione di Noto, Contrada
Renna, IT-96017 Noto (SR), Italy
Gino Tuccari · Walter Alef · Sven Dornbusch · Laura La Porta ·Helge Rottmann · Alan L. Roy · Jan Wagner · Michael Wunderlich
Max Planck Institute for Radio Astronomy, Auf dem Hügel 69,
DE-53121 Bonn, Germany
Rüdiger Haas · K.-Å Johansson
Onsala Space Observatory, SE-439 92 Onsala, Sweden
Laura La Porta also at
Reichert GmbH/BKG, Hittorfstr. 26, DE-53129 Bonn, Germany(Correspondence: tuccari@ira.inaf.it)tion into the existing VLBI environment at telescopeswith a DBBC3 backend.

Keywords Digital Receiver · VLBI · VLBI Backends

1 Introduction
The Digital Base-Band Converter 3 (DBBC3) isthe third generation VLBI backend developed in a
European collaboration under the lead of G. Tuccari(see e.g. Tuccari et al., 2019). The system is modular and, as of today, in a configuration with eightsampler/processor pairs is fully VGOS compliant.
It takes as input eight 4 GHz-wide IFs in the range
0 GHz to 15 GHz. Different channel (sub-band) widthsof 1-2-4-8-16-32-64-128 MHz can be selected fromeach 4 GHz input via Digital DownConverter (DDC)
firmware for output. Alternatively OCT filters allow
the selection of arbitrary parts of the band using 32-tap
FIR convolutional filters acting on the time series fromthe sampler. Filter tap weights have been designed
to produce filter widths of 512 MHz, 1024 MHz and2048 MHz and others are possible by simply loading
different weights into the tap registers. When using
the 2048 MHz filter one can use two filters to cover
the full 4 GHz, which makes this mode compatible
with the R2DBE system used in the Event Horizon
Telescope. The full 4096 MHz band can be output also
without any channelisation. The resulting output data
rates are 16/32/64/128 Gbps.
For the European VLBI Network (EVN) the
DBBC3 shall replace the DBBC2 using its backwardcompatible modes, and at the same time open the27

28

Fig. 1: DBBC3 VGOS model: 8 IFs with 8 groups of ADB3

samplers and CORE3 processing boards. This unit can deliver
128 Gbps with 2-bit samples (output limit is 512 Gbps).

avenue to observations with data-rates up to 32 Gbps,
possible with EVN’s widest IFs at higher frequencies.

2 Modifying the DBBC3 for the BRAND
project
The BRAND EVN project is a EU-sponsored engineering research effort to develop and build a prototype
receiver with a frequency coverage from 1.5 GHz to
15.5 GHz (see Alef et al., 2019). The full band will
be sampled in the receiver box without any downconversion. All usable parts of the band will be selectedon the same board as the sampler chip via four powerful FPGA processors. Pieces of up to 4 GHz width represented as 8-bit samples will be sent to the backend
via optical fibres. The overall structure of the data flow
can be seen in Fig 2.
The DBBC3 is used here as an ideal platform
to handle 4 GHz portions of the full 14 GHz input
band for creating compatible VLBI channels with theobserving modes described in the introduction. The
actual bandwidth of the BRAND EVN channels will
be slightly different from VLBI standards due to thedifferent sampling frequencies compatible with thesampler chip. The sampler device includes its own
synthesizer which operates in a restricted range fromwhich sampling clocks can be selected. The value
selected for BRAND, 28.732 Gsps, is not a power of
2 but allows one to derive integer MHz bandwidths

Tuccari et al.

Fig. 2: Four bands (IFs) are fed to the four inputs of the sampler

chip (blue). They are either one of 0 GHz to 14 GHz or 14 GHz
to 15.5 GHz and one of the possible polarisations. In the FPGAs(green) the serial data streams are converted to parallel. Next
step is band selection, then polarisation conversion or other preprocessing. Last the digitised data are streamed to ethernet. In the
DBBC3 (red), standard VLBI channelisation and formatting are
performed with output of the VLBI data to internet or recorders.

in the digital signal processing chain. This leads tochannelised bandwidths of 7/14/28/56/112/224 MHz
out from the digital frontend, from which the OCTor DDC firmware in the DBBC3 selects bands of
4/8/16/32/64/128 MHz (plus optional resampling),
ensuring compatibility with the bandwidths currently
used in VLBI.
The BRAND EVN data flow involving samplingand digital processing can be functionally divided into
two blocks, one placed in the receiver frontend in theantenna and one in the control room where traditionallythe backends are located. For this reason we can define
the first part a digital frontend and the second a digital backend. The distinction is useful because different
functions are performed in the two separated locations.
The main process in the digital frontend part will,in the first implementation, be the formation of 4 GHz
slices as input to the digital backend. The process inthe digital backend will be the normal VLBI processof further channelisation to select sub-bands from the
4 GHz slice, truncating to 2 bits, and producing VDIF
streams for recording.
In more detail, the digital frontend is now the locus directly following the analogue signal path which
consists of antenna, feed, filters, low-noise amplifiers
and other components, all of which bring the signal toa level suitable for the sampler to sample with a nomi-

DBBC3 Towards BRAND

nal 8-bit depth. The digitised data from the sampler arethen converted from serial to parallel streams, filteredwith a 4 GHz OCT filter, decimated, time-stamped, formatted as VDIF with 8-bit depth, and prepared in IP
packets for transmission on 16 10 GE links per analogue input to the digital backend. Four such analogue
inputs are sampled by one sampler chip, coming fromthe four channels carrying the ranges 0-14 GHz/1415.5 GHz in both polarisations from the analogue section of the receiver. (Fig 2).
The resulting data rate from the sampler is huge –more than 900 Gbps. It is transferred from the digital
frontend to digital backend on a large number of optical fibers (64) carrying VLBI standard VDIF packets, which contain also the sampling time information
along with the data packed as the DBBC3 receiving
section requires.
The timestamps inserted by the digital frontend are
the time reference used for later correlation of VLBI
data, therefore the UTC 1 PPS and frequency reference
must be available at the frontend digital receiver, which
includes for instance connecting a GPS receiver to thedigital frontend.
The digital backend DBBC3 will receive the data
into the CORE3H boards via the ethernet connectors
using a dedicated firmware/software to be loaded forthis mode. Subsequent processing proceeds as usual for
the DBBC3 when doing VLBI.
The digital frontend can in principle perform othermore complex operations which will be implemented
in the future, like dynamic OCT filtering for RFI mitigation, broadband polarisation conversion, and otherdesired tasks compatible with the DBBC3 system.
As mentioned above the first version of thefirmware for the digital frontend will be to send 4 GHz
bands to the DBBC3, which requires the so-called
CORE3H2 configuration of the CORE3 boards. The
CORE3H2 makes use of all eight transceivers on-board
in receiving mode. This architecture allows one toreceive 4 GHz bands with 8-bit representation, which
is similar to feeding a CORE3H using the standard
ADB3L sampler boards as in standard DBBC3s.
It is worth noting that if required, there could be fullcompatibility with a standard DBBC3 equipped with
ADB3L sampler boards to be compatible with traditional receivers whose analogue signal is sampled in
the backend. Indeed switching between input data to
the CORE3H boards coming from the local ADB3L or

29

Fig. 3: The FPGA processing board CORE3H can be populatedwith up to eight optical transceivers. They can work as output(standard DBBC3 VDIF streams for recording) and as input tothe FPGA (application for “digital” receivers.

via the digital frontend could be implemented by using
different firmware.
Another architecture could also be chosen when
additional functionality is required. This is for example the case for the digital linear to circular polarisation in FPGA. The conversion is required for the
BRAND receiver, which is linearly polarised, to workwith circularly-polarised VLBI networks. The conversion can be performed in analogue with a hybrid junction after the feed, or in the digital domain with a
Hilbert transform in FPGA to give accurate 90 degree
phase shift over a wide fractional bandwidth. The additional FPGA resources for performing this process
in the CORE3H are not available due to the great demands of the main function of down conversion andpacket forming. A clean solution can be provided byreplacing a number (or all) the ADB3L with additional
standard CORE3H processing boards, if required. Indeed CORE3H boards can be connected in functionalsequence through their optical transceivers. The flexibility of the DBBC3 allows one to configure the system blocks in diverse ways to satisfy the changing andhighly demanding requirements.

3 Conclusions and outlook
We have shown in this article that the DBBC3 is a very
versatile backend. The development to adapt it to the

30

Tuccari et al.

European VLBI Network Symposium & Users Meeting”,
PoS(EVN2018)140
Alef W, Tuccari G, Dornbusch S, et al. (2019) BRAND - A
wideband receiver for astronomy and geodesy. In: R. Haas,
S. Garcia-Espada, J. A. López Fernández (eds.): Proc. 24th
EVGA Working Meeting, 31–36

Fig. 4: The block diagram shows a DBBC3 whose analogue andsampling parts are by-passed by digital signals from the BRAND(or other) digital frontend.

BRAND digital receiver opens a cost-effective path tohandle the data flood which the BRAND receiver willproduce.
At the same time the BRAND digitiser/processor
unit in or close to the receiver box together with themodified DBBC3 backend can be adapted efficiently toother receivers with large bandwidths. One immediate
application will be the triple-band receiver for the highfrequencies 22 GHz, 43 GHz, and 86 GHz. Rather thanrenewing the limited IF cabling of, for instance, the Effelsberg antenna we are planning to sample as much
bandwidth as possible close to the triple-band receiverwith the BRAND sampler/processing unit and transport the IF as digital on fibre, which is much easier. We
use one or two DBBC3s to form channels (sub-bands)
suitable for VLBI correlation. Assuming 8 GHz bandwidth per polarisation and receiver, we could see data
rates of up to 192 Gbps on output.
It should also be noted that the control of the
DBBC3 in this new mode via the Field System1 will
be an extension of the existing implementation, whichshould be cost effective to realise.

References
Tuccari G, Alef W, Dornbusch S, et al. (2019) DBBC3 the new
wide-band backend for VLBI. In: Proceedings of the “14th1

See for instance http://www.metsahovi.fi/pub/evn-om/4fs4.html

BRAND – A Wideband Receiver for Astronomy and Geodesy
W. Alef, G. Tuccari, S. Dornbusch, A. L. Roy, M. Wunderlich, C. Kasemann, M. Nalbach, M. Pantaleev,
J. Flygare, J. D. Gallego, J. A. López Pérez, F. Tercero Martı́nez, G. W. Schoonderbeek, J. Hargreaves,
R. de Wild, V. Bezrukovs

Abstract The BRAND wideband receiver is being
developed with support from the European Union’s
Horizon 2020 research and innovation programme asa part of RadioNet. Its continuous frequency range
from 1.5 GHz to 15.5 GHz makes it a scientifically extremely interesting development for radio astronomy.
But it also covers the VGOS frequencies and evenextends them to lower and higher frequencies. Usedfor geodesy, this could yield results superior to thosethat will be achieved with the traditional four VGOS
bands. If we succeed in modelling an adequate feed
for secondary focus, BRAND receivers could become
the next generation VGOS receiver. It will also allow
to retrofit traditional prime focus antennas to becomecompatible with VGOS antennas. The first half of the
3 1/2-year-term of the project is over, and we give an
Walter Alef · Gino Tuccari · Sven Dornbusch · A. Roy · Michael
Wunderlich · C. Kasemann · M. Nalbach
Max Planck Institute for Radio Astronomy, Auf dem Hügel 69,
DE-53121 Bonn, Germany
Gino Tuccarialso at INAF Istituto di Radioastronomia, Sezione di Noto,
Contrada Renna, IT-96017 Noto (SR), Italy
Miroslav Pantaleev · Jonas Flygare
Onsala Space Observatory, SE-439 92 Onsala, Sweden
Juan D. Gallego · José Antonio López Pérez · Felix Tercero Martı́nez
Instituto Geográfico Nacional
C/General Ibañez de Ibero, Madrid, Spain
Gijs Schoonderbeek · Jonathan Hargreaves · Ronald de Wild
ASTRON, Netherlands Institute for Radio Astronomy,
Dwingeloo, The Netherlands
Vladislavs Bezrukovs
Ventspils International Radio Astronomy Center, Ventpils,
Latvia(Correspondence: alef@mpifr-bonn.mpg.de)overview of the achievements so far and of what has
been planned for the near future.

Keywords VLBI · EVN · Radio astronomy receiver ·Digital backends · Digital receiver

1 Introduction
Under the RadioNet ‘Joint Research Activity’ BRAND
EVN we are developing and building a prototype “digital” VLBI-receiver for the EVN (and other) telescopes.
It will cover a frequency range of more than 1:10
from 1.5 GHz to 15.5 GHz (18 cm to 2 cm wavelength).
It was decided in the proposal phase already to notinclude the 1.4 GHz band due to strong RFI below
1.5 GHz, to limit the size of the expected feed, andby including instead 15.5 GHz to make the 2 cm bandof the VLBA accessible for the EVN (see Fig. 1).
It should also be mentioned that frequencies below
1.5 GHz are in low demand on the EVN. Our proposal
was awarded about 1.5 Me by the EU under contract
730562, but we expect a total cost of close to 2 M e,which implies additional contributions by the partners
MPIfR, INAF/Noto, OSO, UAH/IGN, ASTRON, and
VUC. The project started in January 2017 and will end
in August 2020. The final report with first fringes froma VLBI observation are due no later than December
2020.
The BRAND prototype will be a digital receiver,which means that the radio frequency signal will not
be down-converted for further processing, but the sampling and initial digital processing will happen in thereceiver box. The only analogue parts remaining are the31

32

feed horn, high temperature superconductor (HTSC)
filters and couplers, low noise amplifiers (LNA) andand additional amplification with filtering to prepare
the signal for the sampler.
The sampler will convert the whole band to the digital domain, and the initial processing will select partsof the band that are (mostly) free of interference. The
resulting data will be transported to the VLBI digitalbackend via optical fibres bypassing the legacy IF systems with their narrow bandwidths, thus providing acheap means to achieve higher bandwidths without theneed for upgrading IF systems which is expensive.
The prototype should be a prime focus receiver as
those feeds are most advanced. As a number of EVN
antennas can only be equipped with secondary focus
receivers one task of BRAND is research in secondary
focus feeds. It was decided by the project team to selectEffelsberg for the prototype so as to achieve maximum
visibility for the project.
The big difference to other receivers is that thewhole band will be digitized without down-conversion
using a single chip, so that the signals will pass througha single receiver which should keep the phase relations between all parts of the band intact. This again
will allow real multi-wavelength VLBI for astronomy
with software that will perform the fringe-fitting over
the whole band in a coherent way. Such a fringe-fitteris also being developed under RadioNet in the ‘Joint
Research Activity’ RINGS. Interesting for geodesy is

Alef et al.

that BRAND will extend the VGOS band to lower andhigher frequencies with a high degree of flexibility withrespect to the parts of the band that can be observed.

2 Status of the BRAND project
The work packages of BRAND are organised in a logical way according to the major parts of the receiver:
frontend (analogue, incl. dewar), backend (digital, incl.
firmware), software (receiver control, recording, correlation), final integration (incl. lab and telescope tests
with VLBI observation) (see Fig. 2).
The BRAND EVN project is progressing moresmoothly than expected: feed, HTSC filters andcoupler, LNA, major digital components, and a large
fraction of the firmware are available already. The
design of the dewar and the analogue signal path arefinished.
The first work package “Feasibility survey of EVN
antennas” was finished in June 2017. Its deliverable
was a report with tables of the characteristics of EVN
telescopes as well as RFI measurements. The motivation of this report is to prepare the ground for the
BRAND receivers at all EVN telescopes. The study on“Solutions for secondary focus” antennas is based on
the same motivation.

2.1 Frontend

Fig. 1: In this logarithmic plot the green rectangle shows the fre-quency bands of EVN telescopes that the BRAND receiver will
cover. Frequencies below the BRAND range are rarely observedwith the EVN, and for frequencies above the EVN will probably
adopt “triple-band receivers”.

The Effelsberg 100 m telescope has a difficult geometry for prime focus feeds. Its opening angle is 2 × 79◦
with an f/D ratio of 0.3. The Onsala team achieved a final best result with a Quad-Ridge Flared Horn (QRFH)
feed with a dielectric inset which improves the response at the high frequencies (Flygare et al., 2018).
The average aperture efficiency is about 50 % over thewhole band (Fig. 3) with an input reflection of better
than -10 dB. The simulated SEFD for the feed is comparable to that of the best Effelsberg feeds which reach
20 Jy. The BRAND feed has an SEFD between about
20 Jy and 40 Jy (Fig. 4).
The feed has been manufactured (see Fig. 5) andhas been measured at Onsala. It was found to agree
well with the simulations.

BRAND Wideband Receiver33

Fig. 2: Organigram of the BRAND project. The work packages are organised in a logical way according to the major parts of thereceiver. The feasibility survey and the study of a secondary focus feed are not directly related to the receiver, but support later
EVN-wide installation.

Fig. 3: This figure shows the simulated efficiency of the QRFH

Fig. 4: The SEFD of the simulated QRFH feed is not much worse

feed for Effelsberg (black line).

than that of the best Effelsberg receivers which reach 20 Jy.

2.2 High temperature superconductor
filters
In the feasibility survey it was found that at Effelsberg the RFI is very strong below 1.5 GHz and at
about 1.8 GHz and 2.2 GHz. These frequencies have tobe suppressed with a HTSC filter to protect the LNA

and the sampler from being driven into the non-linear
regime by this RFI.
Our initial attempt to combine these two filters
and the high-pass together with a direction coupler forphase-cal and calibration into one crystal was not successful. In this attempt the notch filters were not deep

34

Fig. 5: The manufactured QRFH feed without the dielectric in-set. The flatness of the feed is due to the very large opening angleof the Effelsberg telescope of 2 × 79◦ .

enough for the existing RFI at Effelsberg. Also thedrop-off below 1.5 GHz was too shallow.
The solution we could realise together with the
manufacturer uses three separate devices to be connected in series: high-pass, notch filters, coupler. This
will result in a slight increase in system temperature.
The two times three devices were delivered in April
2019.

2.3 Low Noise Amplifier
Our partner Yebes/OAN found a solution for amplifying the whole BRAND frequency band with low noiseand low input return loss (IRL). A single-ended LNA
has the lowest noise, but an unacceptably high IRL,
while a balanced amplifier is only a few kelvin noisier with an acceptable IRL. The disadvantage of a balanced amplifier (Fig. 6) is that for two polarisations
four hybrids and four LNAs are needed.
On the other hand having an additional hybrid at
the input of the balanced amplifiers opens the opportunity to use it to convert the linear polarisation to circular, which had initially not been planned. This could
be done with a wideband hybrid junction at the antenna terminals before the balanced amplifier. The hybrid junction approach was demonstrated in Yebes andfound to work well (phase unbalance of ≤ 2.5◦ and amplitude unbalance of ≤ 1.2 dB over the whole band) but
it is critically sensitive to cable length mismatches (aAlef et al.

Fig. 6: The balanced amplifier consisting of two hybrid junctionsat input and output and two LNAs in the middle.

Fig. 7: Block diagram of the receiver box. The digital electronics

in the box on the right needs more than 120 dB of shielding. In
addition a few 100 Watts of heat have to be transported out.

1 mm length difference contributes a phase unbalanceof 27◦ at 15.5 GHz). This development can be used for
BRAND and VGOS.

2.4 Receiver box with cryostat andanalogue signal path
The design of the cryostat and receiver layout has been
finished. It was determined that the feed requires a window with a diameter of 80 cm, which is just doable. A
simulation of the feed with this dewar and window indicate that there will be only little effects on the beam
pattern. Due to the large window the cryostat will bequite heavy ( 150 kg).
The analogue signal path after the first amplifier
stage is standard except for splitting the signal of eachpolarisation into two parts 1.5 GHz to 14 GHz and
14 GHz to 15.5 GHz. This is the preferred scheme tofeed the input signals to the sampler.

BRAND Wideband Receiver

As the sampling and first stage of FPGA processing
should be installed in the receiver box (see Fig. 7) very
high shielding of RFI produced by the digital components of more than 120 dB is required. This can beachieved by a triple box. The heat of up to about 500 W
produced by the sampler and FPGAs has to be transported out, which makes the whole setup very challenging.

2.5 Sampler and FPGA processing
We were able to procure 16 GHz samplers and an evaluation board under a NDA. The samplers were tested
successfully and even surpassed our expectations. The
sampler chip has four inputs, each for the full bandwidth and thus can handle both polarisations. If two
signals of 16 GHz bandwidth are input to the sampler
the output data rate is two times 56 Gsps with 8-bit
samples. For an input bandwidth of 14 GHz the output data rate is only 28 Gsps with 8-bit samples. As our
total usable bandwidth is only two times 14 GHz thissecond possibility is the preferred option.
To simplify the analogue signal chain and avoid
down-conversion the input signal is split as describedin the previous section (2.4), and the 14 GHz to
15.5 GHz are sampled in the second Nyquist zone.
Thus all four input ports of the sampler chip will beused.
We have chosen a two-step approach for mastering
the enormous data rates coming from the sampler to the
FPGA chips. In a first design the evaluation board will
be used for sampling, together with a first version of
the FPGA processing board. Thus we can fairly early
on in the project develop and test the firmware, thatshould receive the multiple linear data streams of sampled data output by the sampler and should reconstruct
the parallel data streams which the FPGA has to process. This is a requirement for processing the data inthe directly connected FPGAs.
The final design of our own sampling/processing
board has started. It will handle both polarisations andthe full bandwidth. One sampler chip with four inputs
sampling 14 GHz will be placed in the centre of theboard. The sampler will be surrounded by four Xilinx
Kintec Ultrascale FPGAs. The processed data will be
output via 64 fibres. The PCB will work in the microwave regime and the input data rate out from the35

sampler is nearly 900 Gbps. This board will have anenormous number of connections and more than 20
layers of which some have to be of high-class microwave material.

2.6 Firmware
The first big block of firmware has to interface thesampler chip with the four FPGA chips. Tests of thisfirmware should start in a few weeks after this conference. A second block will allow the selection of thedesired and usable parts of the band. This process will
also be executed on the board in the receiver box. Under development are two different kinds of firmware: 1)
OCT filters, which are FIR convolutional filters acting
on the time series from the sampler, which will allow
the selection of arbitrary parts of the band and 2) digitaldown-converter firmware. These two firmware blocks
have still to be tested.
The data will then have to be output via the 64 fibres
and sent to the DBBC3 CORE3H backend processing
boards. The required eight CORE3H boards will haveall eight optical fibre connections populated with SFP+
ports. Four of these will also be used for data output
from the CORE3H to the VLBI recoders, or Internet,or the telescope backend system. The latter will be required for using the BRAND receiver in single dishmode. The DBBC3 can generate narrow VLBI subbands to be compatible with existing observing modes.
This firmware will enter test mode soon.
The polarization conversion firmware will be written by ASTRON in a modular fashion so that it caneither be loaded to the first processing stage up in thereceiver or to the DBBC CORE3H boards. A block design is ready and work is proceeding.

3 Conclusions and outlook
So far the development and the engineering of the prototype BRAND receiver has been surprisingly smooth
without any major stumbling blocks.
Integration has to be done still at MPIfR together
with all partners. The receiver will be tested in the lab
as much as possible. Unfortunately none of the partners
has an anechoic chamber where such a heavy dewar

36

can be handled. So we will have to wait for the testingon the telescope to measure the beam of the receiver,its noise and polarisation characteristics. We are planning to perform wide-band VLBI observation preferably with one or more VGOS antennas.
The extremely high output data-rate from the
BRAND receiver of more than 64 Gbps (2-bit samples
for VLBI) will require also modifications to recording
and correlation software. This work package will
be started late in 2019, while efforts to interface the
BRAND data to the Effelsberg backend system are in
the definition phase.
We expect the BRAND prototype to be ready before the end of 2020.

Alef et al.

Acknowledgements This work has received funding from theEuropean Union’s Horizon 2020 research and innovation programme under grant agreement No 730562 [RadioNet].

References
Flygare J, Pantaleev M, Olvhammar S (2018) BRAND: UltraWideband Feed Development for the European VLBI Network – A Dielectrically Loaded Decade Bandwidth QuadRidge Flared Horn, In: 12th European Conference on Antennas and Propagation (EuCAP2018), London, UK, 9–13

The Stability of Delay in VLBI Digital Backends
E. Nosov

Abstract In order to meet the VGOS requirements, theinfluence of instrumental delay variations from scan toscan needs to be limited to 1 ps level. Achieving this requires a certain stability of the equipment in the signal
chain and implementation of a phase calibration system
to measure the remaining delay variations. As the delay instability in electronic devices is strongly related
to temperature fluctuations, both temperature fluctuations and temperature sensitivity of equipment have to
be minimized. The paper focuses on the stability of
VLBI digital backends. It describes the main sourcesof delay variations and provides an estimation of therespective temperature coefficients for backends developed at IAA RAS. Also the paper discusses a convenient way for in-system measurement of the inner delay variations in Multifunctional Digital Backend.

Keywords VGOS · DBE · BRAS · MDBE · Delay stability · Temperature coefficient

1 Introduction
One of the important requirements to the signal chain
of VLBI radio telescopes is the stability of instrumental
delay. To achieve the goal of 1-mm position accuracy
specified in the VGOS project, the instrumental delay
variations should be kept or at least measured with anerror less than 1 ps (Petrachenko et al., 2009). This reEvgeny Nosov
Institute of Applied Astronomy of Russian Academy of Sciences, IAA RAS, Kutuzova emb. 10, Saint-Petersburg, Russia(Correspondence: nosov@iaaras.ru)

quirement, in particular, applies to the digital backend(DBE), as it is a part of the radio telescope signal chain.
Although DBEs are mostly digital devices and, therefore, can not introduce unwanted delay variations to thesignal after it was digitized, they still have some analog
front-end before ADC, as well as circuits for generating and distributing ADC clock signal. Both of themcan influence the delay, and this influence should be
minimized by appropriate DBE design.
The delay instability in electronic devices isstrongly associated with temperature fluctuations.
Maintaining a stable temperature is an obvious way
to improve the stability of the delay, but it can becomplicated when DBE is located in the confined
space of the antenna focal cabin, like Broadband
Acquisition System (BRAS) in RT13 radio telescopes(Nosov et al., 2016). In this case, low sensitivity totemperature fluctuations is essential for DBE. To
achieve this, the DBE designer needs to know thevalues of delay temperature coefficients (TC) for thecomponents of the signal and clock paths in DBE inorder to find the sections that contribute to the error
most and improve them.
The following section provides estimations of
the temperature coefficients of DBE components,
obtained either from measurements performed at IAA
RAS or from s-parameters and datasheets provided
by component manufacturers. This data was used todesign Multifunctional Digital Backend (MDBE) – thenew back end developed for ”Quasar” VLBI-network(Nosov et al., 2019). It helped to significantly reduce
the temperature coefficient of MDBE compared to
BRAS.
37

38

Nosov

These values were calculated by using s-parameters of
the filter, measured at +25◦ C and +100◦ C.
In total, TC of ADC front-end should be significantly less than 1 ps/K, that is in agreementwith the real measurements of available front-ends.
For instance, the temperature coefficient of BRAS
front-end is in a range of 0.1–0.2 ps/K depending on
frequency. The values for MDBE front-end are evensmaller (±0.1 ps/K), and are limited by the accuracyof the measurement technique. In summary, TC of
DBE signal path should not significantly influence theinstrumental delay variations in case of reasonably
stable temperature.

3 Temperature coefficient of DBE clock
path
Fig. 1: Main sources of delay variations in typical DBE.

2 Temperature coefficient of DBE signal
path
Both the signal path and the clock path of DBE can influence the delay stability of observed signal. Typicallythe input signal passes to ADC through some front-end,
that prepares the signal for digitization (Fig. 1). The
front-end may contain different components dependingon particular DBE, but probably it has an anti-aliasing
filter to limit the spectrum of the signal to one Nyquist
zone, attenuator to control the input level, and a balun
to convert the signal to differential form required by
ADC inputs.
Attenuators have a very low group delay (tens picoseconds) and could hardly have significant TC. For
example, the digital attenuator used in MDBE has TC
of about 10 fs/K. This value was calculated from theplot of relative phase versus temperature, provided by
the manufacturer.
Baluns for the required frequency range (up to
2 GHz) also have a low group delay (tens to few hundreds of picoseconds) and therefore will not contributemuch to the total TC.
Wideband filters for required frequency range usually have TC less than 1 ps/K. For instance, the filter
used in BRAS has TC less than 100 fs/K in the mostof bandpass, and about 200 fs/K at cutoff frequency.

Besides the delay fluctuations in the signal path, theobserved delay of the digitized signal depends on fluctuations of the ADC sampling clock. The variations in
the clock signal shift the sampling time, that is considered as the shift of the signal delay in opposite direction. That is adding 1 ps to delay in clock path reduces
the instrumental delay by 1 ps.
Clock path of DBE is based on clock synthesizer,that generates ADC sampling clock from reference
clock. In multichannel systems the sampling clock has
to be distributed over all ADCs in the system by theclock distributor. Both the synthesizer and the distributor have some TC of delay, as well as the transmission
lines in printed circuit boards (PCB), and coaxial cables.
The clock synthesizer for DBE is typically based onphase-locked loop (PLL) integrated circuit (IC). The
manufacturers of PLL ICs do not provide information
about their phase/delay temperature coefficients. The
TC of a particular synthesizer depends on the properties of the IC, and slew rate of the reference and feedback signals. Based on the experience of IAA engineers, the TC of PLL-based synthesizers usually lay inthe range of a few ps/K. ADC clock synthesizer built
for BRAS has quite good TC about 1.2 ps/K. The synthesizer of MDBE was significantly improved and has
TC about 0.2 ps/K.
Specialized clock distributor ICs give the most convenient way to feed the clock signal to all ADCs in
DBE. There are many of them on the market, but only

Backends Delay Stability

39

for some the manufacturers give the temperature coefficient values. Table 1 presents several examples demonstrating the range of values, spreading from a very noticeable 2800 fs/K to negligible 35 fs/K. T hus, carefully choosing the clock distributor during DBE design
can make its influence on the delay stability barely noticeable.
Table 1: Clock distributors with specified TC and maximum fre-quency more than 1 GHzPart number Temperature coefficient, fs/K
AD95082800
ADCLK854
2000
MAX9312500
LTC6953350
SY89112U
150
SY58034U
65
ADCLK954
50
NB7L1008M
35

The delay in PCB transmission lines also varies
with temperature. The propagation delay in stripline
can be estimated as (Johnson and Graham, 2003).
√

εr
,
(1)
c
where εr is a relative permittivity and c is the speedof light. One of the most popular material for PCBs is
FR4, that have εr about 4.5 and its temperature coefficient about 400 ppm/K (Coonrod, 2011). From (1) it
is easy to find that with total length of lines from thereference clock input to ADC clock input being 40 cm
the delay temperature coefficient of the lines is about
0.6 ps/K.
Luckily, there are more advanced PCB materials on
the market. For example, RO4350B material has εr =3.66 and TC of just 50 ppm/K. This material is often
used for high-frequency applications where a relatively
small increase in the total cost of the system is justified by a significantly better performance. The PCBs
of MDBE are manufactured as a mixture of RO4350B(for clock and high-speed lines) and FR4 (for all others
lines) layers. The 40 cm line implemented at RO4350B
has TC of just 0.06 ps/K, that is ten times less than for
FR4. Therefore, with an appropriate PCB material the
TC of PCB lines is negligible. It should be noted thatfor microstrip lines the PCB material does less contribution to the propagation delay, and the appropriate TC
will be even less than for stripline.
T pd =

Besides PCB lines, DBE can also contain coaxial
cable assemblies. Long coaxial cables in antenna cableloop can cause significant instability of delay, but not in
the case of DBE. Usually the length of the cable assemblies in DBE, if any, is much less than 1 meter. Even
PTFE-based cable, that has so called temperature kneeat room temperature (Czuba and Sikora, 2011), is notable to cause noticeable delay instability. For instance,
15 cm of SM141FEP cable has TC of about 30 fs/K atroom temperature, which is negligible in comparison
to the other sources of instability.
The ADC itself can also cause some instability ofdelay, but at the moment I have no data about the temperature coefficient of any high-speed ADC. It will bemeasured for MDBE in 2020.

4 Temperature coefficients of BRAS and
MDBE
Based on the information above, we can estimate thetotal TC of BRAS and MDBE clock paths (Table 2).
As the influence of signal path is negligible, the total
TC of the systems will be almost the same as in the table, but with the opposite sign. There is no information
about TC of the clock distributors used in BRAS, but
we know the values for similar distributors and can use
it for an approximate estimation. As was mentioned, atthe moment we also don’t know the TC for the ADCs.
Table 2: Estimation of temperature coefficients for BRAS and

MDBE
Part
BRAS
MDBE
Clock synthesizer 1.2 ps/K 0.2 ps/K
Clock distributor 2 ps/K
0.05 ps/K
PCB
0.6 ps/K 0.06 ps/K
ADC
Total
> 3.8 ps/K > 0.31 ps/K

Table 2 shows that BRAS would have TC of morethan 3.8 ps/K while really measured value for BRAS isabout 4.5 ps/K, i.e. close to the estimation. As you cansee in the Table 2, from the stability point of view eachpart of MDBE was significantly improved in comparison with BRAS. The real measurements will be performed in the beginning of 2020, and MDBE has specialized calibration circuits to simplify this measurements.

40

Nosov

5 Internal delay measurement in MDBE
The ADC used in MDBE needs some calibration signal, preferably a tone, to calibrate gains, voltage offsets
and clock phases of its internal cores. One of the possible options to generate such signal is to use a divided
copy of the sampling clock (e.g. 256 MHz) available inthe clock synthesizer. This signal, properly prepared,
is distributed over ADCs in MDBE and measured by
PCAL extractor unit in FPGA. The received information about phase and amplitude of the signal is used tocalibrate the ADC, but it also can be used to monitor
the stability of internal delay.
Figure 2 explains the calibration circuits. The calibration signal comes from either the input clock distributor (100 MHz) or the clock synthesizer (256 MHz)and goes to the ADCs through additional clock distributor IC. This IC is placed close to the ADC clock
distributor (2048 MHz), and thus has almost the same
temperature. The length of all lines is aligned. For thecase of 256 MHz signal it means that instabilities influencing the calibration and ADC clock signals are almost the same. The observed variations of the phase(initial phase is insignificant and not shown), expressedin units of time (∆t1 ), are actually the difference between variations of the calibration signal and the ADC
clock signal:∆t1 = ∆tin + ∆t synt + ∆tdist + ∆tPCB − ∆tclk ,where ∆tin , ∆t synt , ∆tdist and ∆tPCB are delay variations in input clock distributor, clock synthesizer, sampling clock distributor, and clock lines in PCB correspondingly. The variations of ADC clock ∆tclk consistof almost the same parts:

Fig. 2: Embedded delay measurement circuits in MDBE.

As a result, the measured value ∆t2 shows the delay
variations in both synthesizer and ADC:
∆t2 = −∆t synt − ∆tADC .
Periodic measurements of ∆t1 and ∆t2 allow to control the delay variations in the clock synthesizer ∆t synt
and in the ADCs ∆tADC . Adding one more clock distributor allows measuring also ∆tdist and ∆tPCB , thoughthese variations are expected to be insignificant (lessthan 100 fs/K). As signal to noise ratio is high, the expected accuracy of the measurements is much better
than 1 ps. This was approved by modeling with digitization effects taken into account.

∆tclk = ∆tin + ∆t synt + ∆tdist + ∆tPCB + ∆tADC .
Consequently, the measured value ∆t1 directlyshows the variations in ADC:
∆t1 = −∆tADC .
In case of 100 MHz signal used for measurements,
it will contain the same components as 256 MHz signal
except variations of the clock synthesizer ∆t synt :∆t2 = ∆tin + ∆tdist + ∆tPCB − ∆tclk

6 Conclusions
VLBI digital backends can have temperature coefficient of delay as high as several ps/K, what is noticeable for VGOS applications and can influence overall
instrumental delay. The variations in a DBE are included in overall instrumental delay, that normally is
to be measured with phase calibration system. Nevertheless, it is always preferable to keep the variations

Backends Delay Stability

small. An analysis of instability sources in DBEs has
allowed to make the temperature coefficient of MDBE
several times better than for BRAS. The remaining instability of MDBE is measured by embedded calibration circuits that help to separate internal instabilities
from the variations of the input signal. It gives the stations a convenient tool to control the signal chain performance.

References
Petrachenko B, Niell A, Behrend D, et al. (2009) Design Aspectsof the VLBI2010 System. Progress Report of the VLBI2010

41

Committee. NASA Technical Memorandum, NASA/TM2009-214180, 58 pp.
Nosov E, Melnikov A, Marshalov D (2016) Operating Experience of Broadband Acquisition System on RT-13 Radio
Telescopes. In: D. Behrend, K. D. Baver, K. L. Armstrong(eds.): IVS 2016 General Meeting Proceedings, NASA/CP2016-219016, 53–57
Nosov E, Ivanov D, Ipatov A, et al. (2019) Extending of”Quasar” VLBI-network: VGOS-compatible radio telescopein Svetloe. In: K. L. Armstrong, K. D. Baver, D. Behrend(eds.): IVS 2018 General Meeting Proceedings, NASA/CP2019-219039, 12–16
Johnson H, Graham M (2003) High-speed Signal Propagation:
Advanced Black Magic. Prentice Hall Professional
Coonrod J (2011) Understanding When To Use FR-4 Or HighFrequency Laminates. Onboard Technology, 25–30
Czuba K, Dominik Sikora D (2011) Temperature Stability of
Coaxial Cables. Acta Physica Polonica A, 119(4), 553–557

A Simulator to Generate VLBI Baseband Data in Matlab
J. Gruber, J. Böhm, A. Nothnagel, M. Schartner

Abstract VLBI radio telescopes represent a sophisticated interconnection of electronic devices. The final
product of each observation by a radio telescope is the
baseband data. In this presentation, we show a softwaretool as part of the Vienna VLBI and Satellite Software(VieVS) which generates simulated VLBI baseband
data. This simulator is written in Matlab and contains atelescope model which is based on the parametrizationof real antenna key characteristics. Moreover, source
characteristics such as the signal structure from satellites as well as spatial velocities of sources and receivers are taken into account in the model. Advanced
Digital Signal Processing (DSP) algorithms of Matlab are applied to model the antenna system. We will
present the various model components of the simulator and discuss potential applications of such a tool.
Finally, we show the first results of simulation experiments with the processing in a real VLBI processing
chain.

Keywords Baseband data simulation · Correlation

Jakob Gruber, Johannes Böhm, Matthias Schartner
Technische Universität Wien, Department of Geodesy andGeoinformation, Gußhausstraße 27-29/E120, AT-1040 Vienna,
Austria
Axel Nothnagel
Universität Bonn, Institut für Geodäsie und Geoinformation,
Nußallee 17, DE-53115 Bonn, Germany(Correspondence: jakob.franz.gruber@geo.tuwien.ac.at)

1 Introduction and motivation
In Very Long Baseline Interferometry (VLBI),
baseband data are referred to as the filtered, downconverted, sampled, and quantized electric fieldstrength measurements at each telescope. They represent the final output of each station and act as input
data for the correlator to initialize raw data processing.
The digital baseband data file contains the time-tagged
stream of samples recorded at each station. They arecross-correlated to determine the fundamental VLBI
observable. In this work, we present a software tool
written in Matlab, which generates such data streams
based on the simulation of the VLBI observation
process.
The simulator contains a telescope model which isbased on the parametrization of real antenna key characteristics and a source model that allows the generation of a specific signal structure. The model parameters are described in Chapter 3 and the systematic, theoretical analysis of the methods are presented in Chapter 2. Baseband data are usually stored in a specificformat with a few commonly used format descriptions
available. In Chapter 4 the implementation of such aformat converter (formatter) is shown.
Existing baseband data simulators have alreadybeen successfully used for various studies. The
program called ’enoise’ (Nishioka, 2015) developedby the VLBI group of Academia Sinica Instituteof Astronomy and Astrophysics (ASIAA) has usedtheir simulator to test the zoom band mode of theDistributed FX (DiFX) correlator (Deller et al., 2007).
The simulator ’Datasim’ (Meyer-Zhao, 2018), whichis part of the current DiFX software package, wasused for the simulation of higher sampling rates for
the Atacama Large Millimeter/submillimeter Array
42

Baseband Data Simulator(ALMA). Both simulators use functions implemented
in DiFX and apply them in a reverse engineering way.
In contrast, the presented baseband data simulator isdeveloped from scratch and can serve as an independent data source to test correlation algorithms and newobserving modes.
The software design of this simulator is intended
to be flexible in terms of the source and the antennamodel. With this, various types of input signals canbe modeled and simulations to artificial satellites withspecific signal structures can be carried out. In general,due to the flexible model design and the toolboxes offered by the built-in advanced signal processing routines of Matlab, it is possible to be variable with respect
to the simulation of new VLBI observation scenarios(e.g., signal structures, new observing modes). Using
the formatter to link the simulated baseband data sets
to established correlators, it is possible to pipe simulated data through the real VLBI processing chain. This
enables proofs of concepts and evaluating the technicalfeasibility of simulated observation scenarios.
The development of algorithms for a baseband data
simulator implies the inverse mathematical formulation as they are required for certain operations within
the correlation process. That applies in particular forthe alignment of the telescope data streams due to thedifference in signal arrival times and the fringe-rotation
due to the Doppler shift. This kind of knowledge gain
helps our group to get a better understanding of theoperations within the correlator and might be helpful
for a more significant interpretation of the correlator
feedback. Debugging the observation process to infer acertain antenna behavior from the correlator response
might also be another potential field of study.
In this paper, we focus on the description of thecomputational concept. It provides a general overview
of the realization of an independent and flexible baseband data simulator written in Matlab. In analogy to
the first fringe detection, the Chapter 5 ’First Light’ describes the fringe detection of a first basic observation
simulation with the presented baseband data simulator.

2 Methodology and realization with
MatlabThe baseband data simulator is implemented with Matlab and makes use of the built-in digital signal pro-43

cessing toolbox. The digital signal creation for any
sky-frequency is carried out at baseband. The downconversion from sky-frequency to baseband is not simulated because two times the sky-frequency would be
required for the sampling rate. This means at least asampling rate of 16 GHz would be needed for a signal
composed of frequencies in the low X-band at around
8 GHz. A signal simulation of a rather short simulation
time of one second would already require 16×109 samples, which would exceed the internal memory capabilities of currently used computers. Due to the linearityof the down-conversion it is also possible to carry out
any kind of signal manipulation at baseband without
degrading the simulation process. To apply and simulate signal manipulation arising from any kind of electronic device within the real antenna signal chain, socalled transfer functions are used. A transfer function isa mathematical representation of the signal manipulation in the frequency domain and describes the relation
between the output from the device for possible inputs.
The main computational concept of the presented simulator is contained in the formulation of a transfer functions for the antenna system with its individual electronic devices. The transfer functions are applied on the
input signal to account for any signal delay, amplitude
modification, and phase distortion. The various simulation and modeling possibilities which are currently
implemented are described in Chapter 3.
Currently, the Matlab function randn is used to generate normally distributed random numbers which areused to simulate source noise and receiver noise. A
transfer function with a linear phase term is used to delay the source signals by the difference of signal arrival
times between two telescopes. The Doppler shift ismodulated in the time domain using the Hilbert transform. The a priori values for the difference in signal
arrival times and the telescope velocities are calculatedwith the Vienna VLBI and Satellite Software (VieVS)(Böhm et al., 2018). The amplitude scale for source
and receiver noise is defined by the fundamental relation of signal power with the variance of Gaussian
noise. The built-in Matlab Fast Fourier Transformation
fft is used to switch between the time and the frequency
domain. All operations in the simulator are performed
using double precision. In the last step the signal with
64-bit amplitude precision is quantized by the numberof bits defined in the model parametrization (see Chapter 3).

44

3 Model parameters
A variety of model parameters is used to characterize the VLBI observation process within this baseband
data simulator. There are variables to parametrize thesource and the antenna model. Further specifications
with respect to other noise components, the observing
mode, and the observing geometry can also be made.
The source model can be specified by the signal typeof the source, either Gaussian noise or signals with acertain structure (e.g. Differential One-way Ranging
tones). The normalized amplitude of the selected signal is then scaled proportionally by the specified received signal strength. It is characterized by flux density or antenna temperature values. Besides the source
model, the simulator also consists of an antenna modelto account for signal filtering and manipulation. Sensitivity parameters in terms of the noise level within
the receiver can also be simulated choosing real an-

Table 1: Parameter names and their parametrization to configure

Gruber et al.

tenna key parameters like the System Equivalent Flux
Density (SEFD) or system temperature (Tsys). A passband filter can be designed with a built-in Matlab toolbox to account for the amplitude and phase response of
the total antenna system and for the individual electronic components. Phase distortion can be modeledby specifying a variance for phase noise. Other noise
components which affect the antenna system temperature can be modeled by setting individual noise temperatures for the cosmic microwave background, ionosphere and radio-frequency interference (RFI). To define the observing mode, the sampling frequency or observed bandwidth, the number of bits for the digital
signal quantization and the number of channels withrespect to the sky frequency can be selected. The observation duration can also be defined for each station independently. To consider the observing geometry, a delay accounting for the difference in signal arrival times
can be simulated and the Doppler shift due to the relative velocity between the source and antenna platforms
can be modeled. Finally, the date of observation needs
to be specified to link the observation to a point in time.
A more comprehensive list of the model parameters
within the presented baseband data simulator can befound in Table 1.

the presented baseband data simulator
Name
Parameterization
Signal type
Gaussian noise
User defined signal structure
Received signal strength Flux density (Jy)
Antenna temperature (K)Sensitivity
SEFD (Jy)Tsys + effective telescope area (K+m2 ) 4 Storage format and simulation
Sky frequency(Hz)pipeline
Passband filter design∗
Ideal
User definedPhase calibration signal Tone frequency spacing (Hz)In a final step, the filtered, down-converted, sampled
Phase distortion
Variance (rad)and the quantized data stream is converted to a data
System delay(s)format which can be used for further processing at the∗∗Polarization
Circular, linear
correlators. Such a format converter is referred to as
Further noise components (K)formatter and represents one of the key components
Observation duration(s)
Sampling
Sampling frequency (Hz)for the presented simulator. It is capable to provide theBandwidth (Hz)simulation output in a convenient format which can be
Number of bits
(Integer value)
used for correlation in the same way as for real baseNumber of channels(Integer value)band data. The same VLBI processing chain consistingGroup delay(s)of correlation, fringe-fitting, post-correlation processVelocity station 1(s/m)
Velocity station 2(s/m)
ing, and analysis can be fed with either real or simuVelocity source(s/m)
lated baseband data, which allows for profound comDate
YYYY/MM/DDDD/hh/mm/ss
parisons and enables various correlation studies. Such
Source name
Stringa formatter is implemented in Matlab as part of the preStation name 1
2-letter ASCII code
sented baseband data simulator. The used format is theStation name 22-letter ASCII code
∗ filter for each electronic device∗∗ future implementation

VLBI Data Interchange Format (VDIF), which can beread by commonly used correlators such as the Distributed FX (DiFX) correlator. The basic VDIF struc-Baseband Data Simulator

ture consists of data frames, each containing a short
self-identifying data frame header, followed by a dataarray (containing the actual samples). The Matlab formatter is capable to play back the VDIF format andalso supports multi-channel recording and recording ofseveral bits per sample. Once the simulated baseband
data is stored in the VDIF format, it can be used forfurther processing. In this work we use DiFX and theHaystack Observatory Postprocessing System (HOPS)
to correlate and carry out a delay estimation of the simulated baseband data sets. Besides the VDIF database,also a simple but sufficient VLBI Experiment (VEX)
file is generated automatically. It matches the simulated
observation parametrization and can be easily used forthe DiFX correlation and further processing. Table 2
shows the software packages and databases used in therealization of our simulation pipeline.
Table 2: Software packages and databases involved in the simu-

lation pipeline.
Model parametrization ASCII file
Baseband data simulator Matlab program
Baseband data sets
VDIF format
Correlation
DiFX correlator
Fringe-fitting
fourfit

5 First Light
The presented baseband data simulator is the first software solution written in a higher level programming
language which is independent of computation algorithms of existing correlators. Figure 1 shows the resultof a simple observation simulation and serves as a test
object for a basic evaluation of the algorithms within
the simulator.
The simulation is based on a scenario with aradio source radiating Gaussian noise observed by
two telescopes with realistic SEFD values of 3000 Jy
at both telescopes. The telescopes are placed at thesame location to isolate the results from Earth rotation
effects and large baselines delays. This concept isreferred to as zero-baseline observation. Results fromnon-zero-baseline observations are not describedwithin this work and will be subject to other studies.
The rather short observation duration for the presented
test simulation is set to two seconds to work aroundmemory issues. One bit is used for quantization and asampling rate of 32 MHz is applied. The sky frequency
is set to 8212.99 MHz. In order to compensate for the45

short observation time but to secure a fringe-detection
the source flux is increased up to 150 Jy. The fourfit
SNR estimation after the correlation with DiFX yields
a value of 201 while the apriori SNR calculation using
the model parameters yields a value of 221. Taking
into account the sophisticated SNR calculation withan uncertain determination of the efficiency factors,
the values are in a good agreement, which indicates aproper amplitude scaling for the simulated receiver andsource noise. A delay of −123 ns is applied for Stat1
to evaluate the implemented delay application method.
The estimated delay yields a value of −121 ns. This
comparison indicates a proper application of the linear
phase term in the simulation process. The differenceof 2 ns might be due to a different fringe-referencetime which shifts the delay to another point in time,
whereas the delay rate absorbs the remaining difference. An ideal passband filter design is applied for thissimulation to model the antenna frequency response.
The amplitude and phase spectrum of the correlation
function also shows a flat behavior which indicates that
all applied algorithms do not manipulate the resulting
amplitude and phase spectrum. The drop in amplitude
for the last sample might be due to the sampling of
the frequency spectrum and cannot be seen for finer
spectral resolution within the correlation process.
The comparison between expected and real processed values shows a good agreement in general. The
remaining discrepancies can arise from various error
sources, which might not specifically be dedicated tothe simulator algorithms. The used concept of very
short observation time and the zero-baseline observation might have some impact and might cause an unusual behavior within the correlation and fringe-fitting
process. With the increased source flux value to compensate for the short observation time, the ratio of thesource noise amplitude and receiver noise amplitude
gets larger than usual. Some further investigations are
required to verify the application of short observationintervals.

6 Conclusions and outlook
The presented basic evaluation of amplitude scaling,
delay application, and passband filtering serves as thefirst proof of concept for the baseband data simulator
written in Matlab. It shows that it is possible to realize
such an implementation with a higher level program-46

Gruber et al.

Mk4/DiFX fourfit 3.18 rev 2251

1849+670.0P8ZWV, 024-1221, WY
Stat1 - Stat2, fgroup X, pol RR
Fringe quality 9
Error code H
201.1
SNR
2.000
Int time
406.760
Amp
133.8
Phase
0.0e+00
PFD
Delays (us)SBD -0.121814
MBD -0.000071
Fringe rate (Hz)0.000158
Ion TEC 0.000
Ref freq (MHz)8212.9900
AP (sec) 0.500

Amp. and Phase vs. time for each freq., 5 segs, 1 APs / seg (0.50 sec / seg.), time ticks 1 sec

eint12Exp.
Exper # 16383
Yr:day 2019:024
Start 122124.00
Stop 122126.50
FRT 122125.00
Corr/FF/build
2019:183:122135
2019:183:122459
2018:198:095349
RA & Dec (J2000)
18h49m16.0723s+67˚05’41.680"

Fig. 1: Fourfit output of simulated baseband data after correlation with the DiFX software. The plot shows the correlation functionin the time domain with a distinct peak in green color, the delay rate function in red and a flat amplitude and phase spectrum in blue
and red. The simulation setup is configured as follows: two seconds observation time, one-bit quantization, 32 MHz sampling rate,
150 Jy source flux, 3000 Jy SEFD for both telescopes, ideal bandpass filtering, 123 ns delay application.

ming language from scratch without dependencies on is still the possibility to use the supercomputing infrasU
existingValidity
correlators.
The built-in routines randn, fft and tructure at TU Wien, but it would be much more efL
the filter design toolbox prove to be a handy founda- ficient to obtain reliable correlation results with short
WYtion for such a digital signal processing software real- observation intervals as well.
Future work regarding softwareFreqdevelopment
will
ization. With8212.99
VLBI baseband data being characterized
(MHz)
133.8
Phase
Ampl.
obby very high405.0
data rates, memory issues for any kind of address the implementation of non-zero-baseline
57.2
Sbd boxU/L 5/0
APs usedservations
andthepossibility
tosimulate
linearpolarsoftware realizationareunavoidable
andnotrelatedtoW -inf
PC R delays (ns)-inf
R delays (ns)ofphasegreat interest in
Matlab. ItW:YisY a0:0
problem for other (proprietary) program- ized observations. This could be PC
PC
W:Y 0:0
Manl PCW 0
PC amp for VGOS obtestingthemulti-banddelay
estimation
ming languages
as
well.
Of
course,withrespect
to
the
Y 0
X00UR
Chan ids
run time ofW theprogram, other languages will have ad- servations.
X00UR
Chan ids
Yvantages in contrast to higher level programming lanGroup delay (usec)(model)-3.40698065367E-03
Apriori delay (usec)-3.33584943349E-03
Resid mbdelay (usec)-7.11312E-05+/- 1.7E-04
delay (usec) some -1.25149849433E-01
clock (usec)
0.0000000E+00
Resid sbdelay (usec)-1.21814E-01+/- 1.7E-04
guages.Sband
However,effort has beenApriori
madeto apply
Phase delay (usec)-3.29060263253E-03
Apriori clockrate (us/s)
0.0000000E+00
Resid phdelay (usec)
4.52468E-05+/- 1.9E-07
Delay rate (us/s)-8.72267930228E-08
Apriori rate (us/s)-1.06426793023E-07
Resid rate (us/s)
1.92000E-08+/- 1.3E-07
References
parallelTotal
computingstrategies to keep
simulation
phase (deg)-9.2 theApriori
accel (us/s/s) run -1.19603749149E-11
Resid phase (deg)
133.8
+/0.6
Pcal mode: MULTITONE, MULTITONE PC period (AP’s) 5, 5Theor.
Amplitude
406.760 +/- 2.023
RMS
time short.
ph/seg (deg)
0.3
0.6
Search (16X8)
405.022
Pcal rate: 0.000E+00, 0.000E+00 (us/s)
sb window (us)-1.000 1.000
amp/seg (%)
1.1
1.1
Interp.
0.000
Bits/sample: 1x1
SampCntNorm: disabled
mb window (us)-0.000 0.000
ph/frq (deg)
0.0
0.3
Inc. seg. avg.
405.001
Sample rate(MSamp/s): 32
dr window (ns/s) -0.010 0.010
amp/frq (%)
0.4
0.5
Inc. frq. avg.
405.017
Data rate(Mb/s): 32
nlags: 64
t_cohere infinite ion window (TEC) 0.00 0.00
W: az 341.9 el 60.5 pa 142.9
Y: az 341.9 el 60.5 pa 142.8
u,v (fr/asec) 0.000 -0.000
simultaneous interpolator
Control file: default Input file: /fhgfs/global/lv71175/meq/DATA/testscancs/EVGA_proceedings_paper/correlation/1234_1/024-1221/WY..0P8ZWV Output file: Suppressed by test mode

We see a lot of potential application for the simulation of new observing modes and in particular forsatellite observations. The simulation pipeline can beused to test correlators with special observation setup
and source characteristics. The evaluation of correlation results with short duration and large source amplitude in comparison to commonly used longer observation time seems to be an important field of study for
efficient and memory inexpensive simulations. ThereBöhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry. PASP,
130, 044503, doi:10.1088/1538-3873/aaa22b.
Meyer-Zhao Z (2018) Datasim – A VLBI baseband data simulator. DiFX User and Developer Workshop 2018, Wettzell
Nishioka H (2015) DiFX activities at ASIAA. DiFX User andDeveloper Workshop 2015, Hobart
Deller A T, Tingay S J, Bailes M, et al. (2007) DiFX: A Software Correlator for Very Long Baseline Interferometry Using Multiprocessor Computing Environments. PASP, 119,
318–336, doi:10.1086/513572

Optical Fiber Links Used in VLBI Networks and Remote Clock
Comparisons: the LIFT/MetGesp Project
R. Ricci, M. Negusini, F. Perini, C. Bortolotti, M. Roma, R. Ambrosini, G. Maccaferri, M. Stagni, M. Nanni,
E. Kravchenko, M. Siciliani de Cumis, L. Santamaria, G. Bianco, C. Clivati, A. Mura, F. Levi, D. Calonico

Abstract The synchronization between atomic clocks
plays an important part in both radio astronomicaland geodetic Very Long Baseline Interferometry, as
the clocks are responsible for providing time andfrequency reference at radio stations. The availabilityof highly stable optical fiber links from a few radio
observatories and their national metrological institutes
has recently allowed the streaming of frequencies fromoptical clocks based on the Sr/Yb lattice technology(even two order of magnitudes more stable thanH-maser clocks). We will present the current status of
the Italian Link for Frequency and Time (LIFT) andthe ongoing efforts to realize a geodetic experimentutilizing the radio stations in Medicina and Matera
connected in common clock via the optical fiber link.
We will then show the results from the latest VLBI
clock timing experiments also making use of the LIFT
link to compare atomic clocks of the three italian radio
VLBI antennas (Mc, Sr and Nt) using the rms noise in
the interferometric phase. VLBI clock timing proves
more effective than Global Navigation Satellite System
and less expensive than Two-Way Satellite Frequency
and Time Transfer in synchronizing remote clocks.

Roberto Ricci · Monia Negusini · Federico Perini · Claudio Bortolotti · Mauro Roma · Roberto Ambrosini · Matteo Stagni ·Mauro Nanni · Evgeniya Kravchenko
INAF-Istituto di Radioastronomia, Via Gobetti 101, Bologna, IT40129 Italy
Cecilia Clivati · Alberto Mura · Filippo Levi · Davide Calonico
Istituto Nazionale di Ricerca Metrologica (INRiM), Via delle
Cacce 91, Torino, IT-10135 Italy
Giuseppe Bianco · Mario Siciliani de Cumis · Luigi Santamaria
ASI-Centro di Geodesia Spaziale “Giuseppe Colombo” Località
Terlecchia snc, Matera, IT-75100 Italy(Correspondence: ricci@ira.inaf.it)

Keywords Instrumentation VLBI · Optical fiber · Frequency reference dissemination · Atomic clock timing

1 Introduction
Three are the main research areas in which frequency
reference dissemination is important: (i) radioastronomy, (ii) relativistic geodesy and (iii) clock metrology.
In radioastronomy time and frequency optical fiber
links can offer faster operations, they will provide morestable clocks for mm-VLBI operating above 80 GHz(where the H-maser clocks are an important limit tophase stability together with atmospheric turbulence
and a limit to the resolution, see (Rioja et al., 2012;
Nikolic et al., 2013) for a reference. Existing mmVLBI telescopes in Europe that could benefit from highstability in optical fiber links are in Germany (Effelsberg), Spain (IRAM and Yebes), Sweden (Onsala) andFinland (Metsahövi): better (angular) resolution frommm-VLBI runs including these observatories will positively affect the study of radio jets in compact radio sources. Moreover, in geodetic VLBI, in order toachieve 1-mm positioning accuracy clock uncertaninty
at 10−16 are required (Neill et al., 2005). The study ofradio pulsar will also gain through absolutely accurate
time provided by fiber-optic streamed frequency references (Lyne et al., 2016).
The most performing clocks at the moment are optical clocks which utilize a transition in the optical bandinterrogated by a highly stable laser in a ultra cooled(µK) lattice of Strontium or Ytterium (Ushijima et al.,2015). The frequency stability and accuracy of the best
optical lattice clock is nowadays about two order ofmagnitudes better (a few parts in 10−18 after a few
47

48

1000 s of operation). This huge accuracy and stability can be put to the use also in the field of relativistic
geodesy, an example of which is chronometric levelling where the gravitationally shifted frequency difference of two portable optical clocks can determine theiraltitude difference with an accuracy of ∼ 10 cm (Grotti
et al., 2018). Optical fiber links are used to remotelycompare the clocks.
The third reason to operate long-haul highly stable optical fiber links is clock metrology (Lisdat etal., 2016). Apart from the italian case, France, Germany, the UK and Poland are equipping themselveswith optical fiber links to connect each other’s national metrological institutes. This will make possible the comparison of highly performing optical lattice clocks across Europe. At the same integration time
the optical links are orders of magnitude more stable
than satellite-based frequency reference dissemination
techniques such as Global Navigation Satellite Systems
and Two-way Satellite Frequency Transfer. This international optical fiber network for clock metrology willbring to the redefinition of the SI second in the near
future (Riehle, 2017).

2 Method
The MetGeSp (Metrology for Geodesy and Space)
project is an offshoot of the LIFT (Italian Link for
Frequency and Time) infrastructure. MetGeSp aims at
disseminating a highly stable and accurate frequency
reference signal via an optical fiber link to a seriesof Italian facilities. The Italian National Institute ofMetrology (INRiM) in Turin generates the frequency
reference which is streamed via the LIFT link to
Modane (under the Frejus tunnel) to study relativistic
geodesy, to the Milan Financial District, to the INAFIstituto di Radioastronomia radio station for radio
and geodetic VLBI experiments, to Florence’s Italian
Lab for Non-linear Spectroscopy (LENS) for tests on
optical clock frequency accuracy, to the Fucino Plain(Telespazio Facility) for global satellite navigation(Galileo network) and finally to Matera (Centre forSpace Geodesy). The creation of a common clock
between the Medicina and Matera radio stations is themain radio-VLBI related goal of the MetGeSp project(see Section 5).

Ricci et al.

A detailed description of the optical fiber link
would be beyond the scope of this paper. Briefly
the RF signal generated by the INRiM clock is
up-converted to the frequency of a 1.5 µm laser via
an opto-electronic device (an optical frequency comb)
and the phase is kept synchronized via a phase-locked
loop. The laser signal is beamed along a dedicated(dark) fiber. In order to prevent signal attenuation
Erbium-doped Field Amplifiers (EDFAs) are set along
the link. A remote control in Turin is used to minimize
gain instabilities over time in the EDFAs. Excellent
noise cancellation is achieved via a round-trip servo
mechanism which allows to reach a frequency stabilityof the order of 10−19 in terms of Allan deviation
over 1000 seconds. On Nov 7th 2018 the LIFT link
saw its first light in Matera CSG (Fig. 1). With aspan of 1800 km LIFT is now one of the longest
frequency reference dissemination link in the world.
The total span between Turin and Matera is covered in
4 legs and the laser signal is regenerated in Medicina,
Florence (LENS), Pozzuoli (Institute of Optics) andMatera (ASI-CSG). In Matera and Medicina the signal
is down-converted via another optical frequency comb
to the RF domain. The resulting RF (5 MHz, 10 MHz
and 1 PPS) are used directly in the VLBI receiverchain and for remote clock comparison. More details
are found in Calonico et al. (2014) and Clivati et al.
(2015).

Fig. 1: First light of the LIFT link in Matera: Ma-Mc H-maser

comparison via the power spectral density

VLBI, Clocks and Optical Fibers

3 Results
The first VLBI test making use of the LIFT optical fiber
link between the Medicina radio station and Turin was
the geodetic experiment EUR137 in September 2015
(published in Clivati et al. (2017)): the local and remote H-maser frequency signals were alternately injected into the VLBI data acquisition chain and the datafrom the two clocks were analyzed as two separate experiments.
In order to further test the VLBI and link set-up inview of a common-clock experiment between Medicina and Matera stations two 24 hour-long S/X-band
geodetic experiments were carried out on in July 2017
and April 2018 utilizing the Medicina, Noto and Matera stations. Medicina received the frequency signal
from Turin for the all duration of the runs. The data
were correlated in Bologna with the local DiFX correlator (Deller et al., 2007) and fringe fitted using theHaystack Observatory Post-processing Software fourfit (Cappallo, 2017). The geodetic tools CALC/SOLVE
and nuSolve (Bolotin et al., 2014) were used to analyze
the correlated data. In the former of two test sessions
a few unlocks were found and fixed at the geodetic
analysis stage. The latter geodetic session ran smoothly
without any link unlocks, but problems with correlating
Noto scans resulted in the usage of only the MedicinaMatera observation pairs in the geodetic analysis. The
group delay weighted rms residuals after station, clock
and atmosphere model subtraction are 56 ps on the McNt baseline and 46 ps on the full July 2017 experiment.
An alternative way to study remote clock synchronization using VLBI antennas makes use of the statistics of the interferometric phase (Krehlik et al., 2017).

Table 1: Summary of the VLBI clock timing observations:49

To this purpose a series of VLBI clock timing experiments were performed with a network comprising the stations of Medicina, Noto, Matera, Yebes andMetsähovi in January/February 2018 (Effelsberg station accepted to take part in one run but it was windstowed for the full time). Many factors contribute to thedeterioration of the interferometric phase stability, themost important being atmospheric instabilities, gain elevation effects and antenna thermal deformations. In
order to minimize these performance degrading effects
the VLBI runs were carried out at night during the winter months on a point-like radio source (15-min scansin 3-hour runs at medium/high antenna elevation tominimize air mass absorption). In Table 1 we report asummary of the VLBI clock timing observations. The
VT007-9 experiments were 6 hours long on two calibrator arcs and were carried out in February 2019.
The S/X-band observations (VT001 and VT007)
were performed with the stardard geodetic frequency
set-up and bit rate. The C-band observations were performed with a radio astronomical VLBI frequency setup: the observing band was split into 4 contiguous 8MHz wide sub-bands (IFs) of 32 frequency channels
each just below the sky frequency of 5 GHz. The Chi observations set-up has 8 4-MHz wide contiguous
sub-bands in dual polarization mode at a centre frequency of 6.7 GHz. The Bologna DiFX correlator wasused to correlate the station data which were then read
into FITS files. The fringe fitting and frequency averaging were done in AIPS (Greisen, 2003). The data wereread out from AIPS into ASCII tables and the statistics
on the phase stability were computed scan-by-scan according to Krehlik et al. (2017): the scan samples wereseparated into couples (even statistics) and triplets (oddstatistics) and then first differences and interpolatedvalue differences were computed together with theirroot mean square. The C/C-hi band experiments had
2-bit sampling and 1-sec time integration. The central
80 % of the bandpass was used in the analysis, thus removing the less sensitive sloping wings. The time synchronization was computed using the formula:project codes, the observing dates, the stations involved, thebands used and whether the Medicina station was receiving or
not the remote frequency standard from INRiM. Baselines with
Metsahövi could not be correlated because of a data format problem.
∆φrms
Project code Date stations
Band Mc rem clock?
∆trms =,
VT001
20180118 Mc,Nt,Ma,Ys,Mh S/X
No
2πν0
VT003
20180124 Mc,Nt,Tr
C
No
where ∆trms is the rms time synchronization beVT005
20180219 Mc,Nt,Tr
C
No
tween
clocks, ∆φrms is the phase rms noise and ν0 is
VT006
20180220 Mc,Nt,Tr,Ys
C
Yes
VT007
20181123 Ma, Eb, On
S/XNo
the sky centre frequency in each sub-band. The results
VT008
20190205 Mc, SrC-hi
Yesof the VT008/9 experiments are shown in Table 2. The
VT009
20190204 Mc, Sr
C-hi
No

results are in good agreement with Krehlik et al. (2017)

50
Table 2: Results of the VLBI timing experiments in C-hi band:the tag rem(loc) means that Medicina was using remote(local)
H-maser frequency reference. Only even statistics is shown.
Project code pol HM ∆trms error bar
VT008
RR rem 3.08 0.03
VT009
RR loc 2.31 0.03
VT008
LL rem 3.79 0.04
VT009
LL loc 2.79 0.03

on the same timescale. We also found similar statistical values for ∆trms for remote and local clocks for the
Medicina station.

4 Conclusions and outlook
The LIFT infrastructure is able to deliver a frequency
reference signal from the Italian Metrological Institute(INRiM) to remote locations via an optical fiber linkwith unprecedented stability (of the order of a few partsin 10−19 in 1000 s integration time based on Allan standard deviation).
Geodetic VLBI experiments are performed with theremote frequency reference provided to the Medicina
radio station. The wrms residuals in the group delays
are in agreement with the statistics found in experiments using local clocks.
The ASI-Centre for Space Geodesy (ASI-CSG) in
Matera was reached by the LIFT link and the first light
was achieved in Matera on Nov 7th 2018. The link
now spans 1800 km of optical fiber in four legs: TurinMedicina, Medicina-Florence, Florence-Pozzuoli and
Pozzuoli-Matera. At the end of each leg the laser signal is regenerated and kept in phase synch.
RMS stastistics on the interferometric phase noise
was successfully used in remote and local clock timing
experiments utilizing the radio/geodetic VLBI technique. The level of synchronization between clocks isestimated to be better than a few pico-seconds over
900-second observing scans in good to excellent observing conditions.
In the near future the following developments areplanned:• a VLBI vs GPS frequency stability analysis in the
CONT14 and CONT17 campaigns focusing in particular on the co-located stations of Matera and
Onsala compared to Wettzell;

Ricci et al.

• a series of common-clock geodetic experiments inwhich both Medicina and Matera stations are going to receive remote frequency reference from
Turin;• a comparison of Japan’s NICT and Italy’s INRiM
optical clocks via VLBI utilizing the portable
Japanese MARBLE 2.4-metre antennas, one ofwhich is at the moment installed at the Medicina
radio station (see Sekido et al., 2019, for details
on this project);• the usage of interplanetary space probe tones andthe ∆DOR (Differential One-way Ranging) technique to compare clocks at two receiving radio stations;• the usage of the LIFT link for possible future VLBI
timing experiments between the Medicine/Turinand Polish Torun/KM-FAMO optical clocks;• the testing of the White Rabbit/Precise Time protocol technology for digital dissemination of frequency reference signals and for clock synchronization.
Acknowledgements We thank the VLBI partners from Yebes
Observatory (B. Tercero Martı́nez, J. González Garcı́a, P.
de Vicente), Torun Observatory (A. Marecki, P. Wolak, M.
Gavroǹski), Metsahövi Observatory (J. Kallunki, J. Tammi),
Effelberg Observatory (A. Kraus, U. Bach), Matera CSG (G.
Colucci, M. Paradiso, F. Schiavone), Noto radio station (P.
Cassaro, S. Buttaccio), Onsala Observatory (R. Haas, J. Yang,
M. Lindqvist), Sardinia Radio Telescope (S. Poppi, G. Surcis)
and the staff of the Medicina radio station for their support
during the VLBI runs.

References
Bolotin S, Baver K, Gipson J, et al. (2014) The VLBI Data
Analysis Software νSolve: Development Progress and Plans
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Calonico D, Bertacco E K, Calosso C E, et al. (2014) Highaccuracy coherent optical frequency transfer over a doubled 642-km fibre link. Appl. Phys. B, 117, 979–986,
doi:10.1007/s00340-014-5917-8
Cappallo R (2017)
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fibre-optic link for Very Long Baseline Interferometry. IEEEVLBI, Clocks and Optical Fibers

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Clivati C, Ambrosini A, Artz T, et al. (2017) A VLBI experimentusing a remote atomic clock via a coherent fibre link. Nature
Scientific Reports, 7:40992, doi:10.1038/srep40992
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Environments. PASP, 119, 318–336, doi:10.1086/513572
Greisen E (2003) AIPS, the VLA, and the VLBA. In: A Heck(ed.): Information Handling in Astronomy - Historical Vistas, Astrophysics and Space Science Library, 285, Springer,
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Grotti J, Koller S, Vogt S, et al. (2018) Geodesy and metrology
with a transportable optical clock. Nature Physics, 14, 437–
441, doi:10.1038/s41567-017-0042-3
Krehlik P, Buczek L, Kolodziej J, et al. (2017) Fibre-optic delivery of time and frequency to VLBI station. A&A, 603, 48,
doi:10.1051/0004-6361/201730615
Lisdat C, Grosche G, Quintin Q, et al. (2016) A clock network
for geodesy and fundamental science. Nature Communications, 7, 1–7, doi:10.1038/ncomms12443
Lyne A et al. (2016) The formation, life and uses of pulsars –nature’s finest cosmic clocks. Proceedings of 2016 European

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Current and Future Requirements for Geodetic VLBI Systems. Report of the Working Group 3 to the IVS Director Board, https://ivscc.gsfc.nasa.gov/about/wg/wg3/IVS
WG3 report 050916.pdf
Nikolic B, Bolton R C, Graves S F, et al. (2013) Phase correction
for ALMA with 183 GHz water vapour radiometers. A&A,
552, A104, doi:10.1051/0004-6361/201220987
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25–31, doi:10.1038/nphoton.2016.235
Rioja M, Dodson R, Asaki Y, et al. (2012) The impact of Frequency Standards on Coherence in VLBI at the Highest Frequencies. AJ, 144, 121, doi:10.1088/0004-6256/144/121
Sekido M, Takefuji K, Ujihara H, et al. (2019) ITA-JPN Broadband VLBI Experiment for Optical Clock Comparison. In:
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ITA-JPN Broadband VLBI Experiment for Optical Clock
Comparison
M. Sekido, K. Takefuji, H. Ujihara, H. Hachisu, N. Nemitz, M. Pizzocaro, C. Clivati, D. Calonico, T. Ido,
M. Tsutsumi, E. Kawai, K. Namba, Y. Okamoto, R. Takahashi, J. Komuro, R. Ichikawa, H. Ishijima,
F. Bregolin, F. Levi, A. Mura, E. Cantoni, G. Cerretto, F. Perini, G. Maccaferri, M. Negusini, R. Ricci

Abstract NICT has developed a broadband VLBI
(very-long-baseline interferometry) system for intercontinental frequency transfer. After domestic tests inJapan, a 2.4 m diameter VLBI station was exported
and installed at Medicina astronomy observatory of
INAF in Italy in 2018. We have started VLBI experiments for optical clock comparison on an Italy-Japan
intercontinental baseline. Reference signals generated
by an ytterbium (Yb) optical lattice clock at INRiM in
Torino and by a strontium (Sr) lattice clock at NICT
headquarters in Koganei are compared by a seriesof links, which include a coherent optical fiber link
between INRiM and Medicina and intercontinental
VLBI observation between Medicina and Koganei.
A series of VLBI experiments was performed from
Oct. 2018 to Feb. 2019. Yb and Sr lattice clocks wererepeatedly operated throughout the same period for
frequency comparison.

Keywords Broadband VLBI · Frequency comparison
Mamuro Sekido · Kazuhiro Takefuji · Hideki Ujihara ·Masanori Tsutsumi · Ejii Kawai
NICT Kashima Space Technology Center, 893-1 Hirai, Kashima
314-8501, Japan
H. Hachisu · N. Nemitz · T. Ido · K. Namba · R. Ichikawa ·H. Ishijima
NICT Headquaters, 4-2-1 Nukui-Kita-Machi, Koganei, Tokyo
184-8795, Japan
M. Pizzocaro · C. Clivati · D. Calonico · F. Bregolin · F. Levi ·A. Mura · E. Cantoni · G. Cerretto
Istituto Nazionale di Ricerca Metrologica, IT-10135 Turin, Italy
F. Perini · G. Maccaferri · M. Negusini · R. Ricci
Institute of Radioastronomy, National Institute of Astrophysics,
IT-40129 Bologna, Italy(Correspondence: sekido@nict.go.jp)

1 Introduction
Driven by fast development of high accuracy opticalfrequency standards reaching 10−18 accuracy (Riehle
et al., 2018), re-definition of the “second” as the unitof time is being discussed in the metrological community (Riehle, 2015). For this, accurate frequency comparison between atomic clocks at distant locations is
an important technology. Frequency transfer by opticalfiber-link reaches uncertainties below 10−18 (Lopez etal., 2012; Predehl et al., 2012; Calonico et al., 2014),
but it requires an infrastructure of suitable fibers and bidirectional optical amplifiers. Two-way Satellite Time& Frequency Transfer (TWSTFT) is another techniqueused for international time and frequency links overdistances of thousands of km. Advanced TWSTFT using carrier phase has a potential to reach instabilities
in the order of 10−17 (Fujieda et al., 2016). This relies on the availability of suitable communication satellites. Limited available bandwidth and high operating
costs are additional drawbacks. Observation of GPS
satellites is routinely used to maintain time links between national time standards agencies. The lowest
uncertainty of frequency links by GPS signals is in
the order of 10−16 , achieved by a technique of precise point positioning processing with integer ambiguity solution(IPPP) (Petit et al., 2015). VLBI is anotherspace geodetic technology with potential for precise
frequency comparison over intercontinental distance.
In contrast to TWSTFT, VLBI is not restricted by theavailability of communication satellites or the requirement of licensed radio transmission. The VLBI technique relies on observing extragalactic radio sourcesof the international celestial reference frame (ICRF).
These form fiducial points in the sky, whereas GPS observations rely on estimated satellite orbits, that vary52

Broadband VLBI for Optical Clock Comparison

with time. High precision GPS processing observes
phase signals that require careful processing to avoid
errors from cycle ambiguities. Broadband VLBI provides an absolute group delay observable that is freefrom ambiguity, and precision in the order of pico seconds. These properties are the foundation for long-term
stable VLBI frequency links. Based on this perspective,
we have developed a broadband VLBI system for anintercontinental frequency link. We expect to achieve
uncertainties in the order of 10−17 with comparing stable hydrogen maser (HM) standards over several daysof time span.
The concept of broadband VLBI observation proposed as VLBI Global Observing System (VGOS) (Petrachenko et al., 2009; Niell et al., 2018) is an innovative system to improve the delay measurement precision by one order of magnitude over conventional
S/X-band VLBI. This is achieved by ten times wider
bandwidth of observing radio frequency. A higher dataacquisition rate contributes to improvement of observing sensitivity as well. Based on these advanced properties, we implemented a broadband VLBI system using small diameter transportable VLBI station for frequency comparison.

2 Broadband VLBI system andobservation scheme
2.1 Broadband VLBI system
Our broadband VLBI system named GALA-V(Sekido et al., 2017) implements the broadband VLBI
concept of the VGOS. Radio telescopes capable ofobserving the frequency range of 3 − 14 GHz areused for observation. The employed observation
mode differs slightly from the prototype VGOS
‘Proof of Concept(PoC)’ implementation (Niell et al.,2018) developed by MIT Haystack observatory andNASA/GSFC. In contrast to the PoC VGOS terminal, which acquires data on more than one hundred
channels with 32 MHz frequency width, we adopted
a simpler data acquisition using four channels of
1 GHz bandwidth. A unique technique in our dataacquisition system (DAS) is the use of RF-Direct
sampling (RFDS) (Takefuji et al., 2012). The observed
radio signal of one polarization is amplified by low

53

noise amplifier and divided into two upper and lower
frequency band, limited to 8192 MHz width by antialiasing filters. Each signal is then digitized at radio
frequency with 16,384 MHz sampling rate. Frequency
selection and band shaping are performed by digital
signal processing implemented in the sampler. Four
streams of 2048 Msps 1 bit quantization data comesout via optical fiber cables as Ethernet packet stream
in VDIF format (Whitney et al., 2014) per single
polarization. Compared to 16 MHz width conventional
S/X-band VLBI, 1024 MHz bandwidth
provides a√sensitivity advantage by a factor of 1024/16 = 8 forsingle channel fringe detection.
The advanced delay precision and sensitivity of thebroadband VLBI open the possibility to utilize small
diameter stations for geodesy and frequency transfer
over intercontinental distances. Besides wideband dataacquistion, we employ joint observation with a large
diameter antenna (R) to compensate the low sensitivityof small diameter antennas (A,B). By using the closure
delay relation, the delay observable of the A-B baseline is composed of a linear combination ofR-A and RB baselines. This scheme is not only useful for using
small VLBI stations, but also for eliminating the delay
variation due to large diameter antennas; such as gravitational distortion and electric cable length variation
due to temperature and stress change. We name thistype of observation “Node-Hub” style (NHS) (Sekido,2017), and have confirmed it by domestic evaluation in
Japan and intercontinental experiments between Italy
and Japan.

2.2 Frequency link with transportablebroadband VLBI station
Prior to the experiments over intercontinental baseline, we evaluated the system in a collaboration between National Metrology Institute of Japan (NMIJ)
and NICT, two national metrological agencies in Japan,that generate the local time scales UTC(NMIJ) andUTC(NICT). These time scales are regularly comparedwith UTC and reported to BIPM. This provides an excellent basis to evaluate the NHS VLBI frequency linkwith respect to the other techniques, and we confirmedthat eliminating the delay variation caused by large diameter antenna indeed results in an improved post-fit

54

delay residual: The experiments show a weighted RMS
of about 10 picoseconds.
The difference of UTC(NMIJ)-UTC(NICT) obtained by precise point positioning (PPP) analysis of
GPS data is routinely published by BIPM (BIPM,
2017). Integer-ambiguity PPP (IPPP) processing(Petit et al., 2015) provides further improvements.
G. Petit and J. Leute of BIPM have courteously
provided IPPP data for the UTC(NMIJ)-UTC(NICT)
time difference. Comparison of double difference data
between VLBI-GPS(IPPP) and GPS(PPP)-GPS(IPPP)
over a 10 days span indicates that the VLBI frequency
link has better performance than GPS(PPP), at least
for long time spans.

3 Intercontinental broadband VLBI
between Italy and Japan
After the domestic experiments in Japan, a 2.4 m
diameter broadband VLBI station (MARBLE1) wastransported to the Medicina astronomy observatoryof INAF/IRA for experiments on an intercontinental
baseline. INRiM and NICT are both operating opticallattice clocks as secondary frequency standards. The
reference frequency generated by the Yb optical latticeclock at INRiM (Torino) is transferred to Medicina observatory by a coherent fiber link (Clivati et al., 2015),
and is used to evaluate a local hydrogen maser (HM).
The HM signal is used as the reference of broadband
VLBI observation with the 2.4 m antenna. In thesame way, a HM at NICT headquarters (Koganei) is
evaluated using Sr lattice clock NICT-Sr1. The HM
provides the reference signal for the counterpart 2.4 m
VLBI station (MARBLE2) at Koganei. The Kashima
34m antenna contributes to this broadband VLBI inorder to improve signal to noise ratio. Observations
between the two small VLBI stations are realized by
the NHS processing scheme. Fig. 1 shows an overview
of the project to link the Yb clock at INRiM and the Srclock at NICT.
The 2.4 m dish and components of VLBI station
were delivered to Medicina in July 2018 and assembled
over the course of few days (Fig.2).
Local infrastructure was prepared by INAF andINRiM, such as optical fiber for signal transmission
to the observation room and access to the high speed
research networks GARR and GEANT. Thanks

Sekido et al.
Table 1: VLBI sessions performed from Oct.2018 to Feb. 2019.

VLBI observation between MARBLE1(Medicina) and MARBLE2(Koganei) is formed by the NHS scheme in joint observation with the Kashima 34 m antenna.
ExpCode Start Time(UT) Length[h] No. Scans
GV8278 05 Oct.2018 07:39
31
593
GV8287 14 Oct.2018 15:35
30
460
GV8297 24 Oct.2018 21:00
29
436
GV8308 04 Nov.2018 02:30
29
464
GV8318 14 Nov.2018 08:00
29
464
GV8328 24 Nov.2018 13:30
29
415
GV8338 04 Dec.2018 19:00
29
471
GV8349 14 Dec.2018 00:30
29457
GV8359 25 Dec.2018 06:00
29
476
GV9015 15 Jan.2019 06:00
29
479
GV9025 25 Jan.2019 03:00
36573
GV9035 04 Feb.2019 03:00
31706
GV9045 14 Feb.2019 03:00
36
786

to the antenna control software FS9 developed by
NASA/GSFC, pointing observations to establish theantenna model were easily realized, along with remoteantenna operation from Japan. An initial fringe test
was conducted with the support of Ishioka VGOS
station of the Geospatial Information Authority ofJapan (GSI). Except for the antenna control of Ishioka
station, all operation (antenna & DAS control, datatransfer, correlation processing) for the fringe test
was performed remotely from Medicina during the
installation visit, and interferometer fringes weresuccessfully detected. The main series of broadband
VLBI experiments via the NHS scheme were thenconducted from Oct. 2018 to Feb. 2019 with session
length about 30 h, repeated at a 10 days interval(Table 1).
Fig. 3 shows an example of the delay residuals of
the VLBI analysis over the Medicina-Koganei baseline. The weighted RMS of the delay residual was 24 psin this case. A peculiar splitting of the delay residualfor radio sources 3C418 and 2022+542 is clearly visible in the plot. Xu et al. (2019) have reported that
3C418 shows strong signatures of radio source structure in group delay measurement. Investigation on calibration techniques for the radio source structure effects has been continued (Bolotin et al., 2019; Xu et al.,2019). Thus we need to minimize the influence of radiosource structure by careful selection of radio sourcesin scheduling the VLBI session until the calibration
method will become widely available.
A detailed discussion of geodetic results and frequency comparisons obtained in these experiments will
be reported in separate publications.

Broadband VLBI for Optical Clock Comparison

4 Summary
A transportable 2.4 m broadband VLBI station was installed at Medicina astronomy observatory of INAF for
an intercontinental frequency link experiment. Precise
frequency comparison between the Yb lattice clockat INRiM and the Sr lattice clock at NICT has been
performed by using intercontinental broadband VLBI,
with local hydrogen masers acting as flywheels. VLBI
sessions were conducted from Oct. 2018 to Feb. 2019with both Yb and Sr clocks operating throughout thesame period. The experiments make use of newly developed signal processing for polarization synthesis
and broadband bandwidth synthesis, and confirmedthat the 2.4 m diameter size radio telescopes achieve a
precision of few tens of pico seconds in NHS measurements over an intercontinental baseline. In addition, radio source structure effects were clearly detected in ourdata. Until a calibration technique for this effect will
become available, we are going to minimize this influ-

55

ence by source selection in scheduling the VLBI session.
Acknowledgements We thank T. Suzuyama and K. Watabe
of NMIJ for supporting development of broadband VLBI tocompare UTC(NMIJ)-UTC(NICT). G. Petit and J. Leute of
BIPM for providing GPS IPPP solution for comparison of
UTC(NMIJ)-UTC(NICT). Quick data transfer of VLBI data
is supported by high speed research network GARR, GEANT,
Internet2, TransPAC, APAN, and JGN.

References
BIPM (2017) Local representation of UTC. BIPM Annual Report on Time Activities, 12, 41, ISBN 978-92-822-2268-3,
ISSN 1994-9405
Bolotin S, Baver K, Bolotina O, et al. (2019) The source structure effect in broadband observations. In: R. Haas, S. GarciaEspada, J. A. López Fernández (eds.): Proc. 24th EVGA
Working Meeting, 224–228

Fig. 1: Overview of the project to compare optical lattice clocks via intercontinental VLBI observation. The Yb lattice clock at

INRiM and the Sr clock at NICT are compared by a series of links including optical fiber link between INRiM and Medicina, andintercontinental VLBI observation between Medicina and Koganei.

Fig. 2: Installation of transportable VLBI station at Medicina. The transportable 2.4 m antenna consists of separate assemblies forthe dish and Az/El drive system. Three persons are sufficient to assemble the system in two days of work (Left and Center). A small
air-conditioned box, located 30 m from the antenna, contains antenna control system(right).

56

Calonico D, Bertacco E K, Calosso C E, et al. (2014) Highaccuracy coherent optical frequency transfer over a doubled 642-km fiber link. Appl. Phys. B, 117, 3, 979–986,
doi:10.1007/s00340-014-5917-8
Clivati C, Costanzo G A, Frittelli M, et al. (2015) A Coherent Fiber Link for Very Long BaselineInterferometry. IEEE
Trans on Ultrason. Ferroel. Freq. Contr., 62, 1907–1912,
doi:10.1109/TUFFC.2015.007221
Fujieda M, Gotoh T, Amagai J (2016) Advanced two-way satellite frequency transfer by carrier-phase and carrier-frequency
measurements. J. Phys. Conf. Ser. 723, doi:10.1088/17426596/723/1/012036
Lopez O, Haboucha A, Chanteau B, et al. (2012) Ultra-stable
long distance optical frequency distribution using the Internet fiber network. Opt. Express, 20, 21, 23518–23526,
doi:10.1364/OE.20.023518
Niell A, Barrett J, Burns A, et al. (2018) Demonstration of a
Broadband Very Long Baseline Interferometer System: A
New Instrument for High-Precision Space Geodesy. Radio
Sci., 53, doi:10.1029/2018RS006617
Petit G, Kanj A, Loyer S, et al. (2015) 1 × 10−16 frequency transfer by GPS PPP with integer ambiguity resolution. Metrologia, 52, 301–309
Petrachenko B, Niell A, Behrend D, et al. (2009) Design Aspectsof the VLBI2010 System. Progress Report of the VLBI2010
Committee, NASA/TM-2009-2014180

Sekido et al.

Predehl K, Grosche G, Raupach S M F, et al. (2012) A
920-kilometer optical fiber link for frequency metrology
at the 19th decimal place, Science, 336, 6080, 441–444,
doi:10.1126/science.1218442.
Riehle F (2015) Towards a Re-definition of the Second Basedon Optical Atomic Clocks, Comptes Rendus Physique, 16,
5, 506–515, doi:10.1016/j.crhy.2015.03.012
Riehle F, Gill P, Arias F, et al. (2018) The CIPM list of recommended frequency standard values: guidelines and procedures. Metrologia, 55, 188–200
Sekido M (2017) Node - HUB Style VLBI with Broadband System. IVS NICT-TDC News 37, 22–25, www2.nict.go.jp/sts/
stmg/ivstdc/news 37/pctdc news37.pdf
Sekido M, Takefuji K, Ujihara H, et al. (2017) Broadband VLBI
System GALA-V and Its Application for Geodesy and Frequency Transfer. In: R. Haas, G. Elgered (eds.): Proc. 23rd
EVGA Working Meeting, 5–9
Takefuji K, Kondo T, Sekido M et al. (2012) High-order Sampling Techniques of Aliased Signals for Very Long Baseline
Interferometry. PASP 124, 1105–1112, doi:10.1086/668232.
Whitney A, Kettenis M, Phillips C et al. (2014) VLBI Data
Interchange Format (VDIF) Specification. https://vlbi.org/
vlbi-standards/vdif/
Xu M H, Anderson J M, Gong S, et al. (2019) Structure
effects in broadband VGOS data. Presentation at the24th EVGA Working Meeting, Gran Canaria www.oan.es/
evga2019/EVGA2019 PDF/O322 EVGA2019 Xu.pdf

Fig. 3: Post-fit delay residual plotted for each source measured by 2.4 m diameter antenna pair over the Medicina-Koganei baseline.
We attribute the split of residual for 3C418 to radio source structure.

Research and Application of VLBI Differential Phase Delays in
Lunar Exploration
X. Zheng, Q. Liu, F. Shu, Y. Huang, P. Li, Z. Xu, Z. Chu

Abstract During the mission of Tracking and Data
Relay Satellite of Chang’e-4 mission (TDRSS-C4) inMay 2018, same-beam VLBI observations between
TDRSS-C4 and Longjiang-2 (Microsatellite B) weresuccessfully carried out by the Chinese VLBI network(CVN) during the Earth-to-Moon transfer section. After data processing and analysis, differential phase delay (DPD) of same-beam VLBI was calculated successfully. Combining ranging, range rate and bandwidth synthesis group delay data, the orbit determination of two satellites were successfully accomplishedby using DPD which continued more than one houron May 22. After orbit determination, the residuals of
DPD were 4.97 ps (BJ-KM), 5.37 ps (BJ-UR), 4.40 ps(BJ-TM), 4.87 ps (KM-UR), 2.97 ps (KM-TM) and3.64 ps (UR-TM), respectively.

Keywords TDRSS-C4 Microsatellite B · Differential
Phase Delay

1 Introduction
The same-beam VLBI technology uses the main-beamof a radio telescope to receive the signals emitted fromtwo satellites simultaneously. After the correlation processing, the phase delays of the two satellites are differentiated in order to calculate the Differential Phase
Xin Zheng · Qinghui Liu · Fengchun Shu · Yong Huang · Peijia Li · Zhijun Xu · Zhanghu Chu
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Nandan Road 80, Shanghai, China(Correspondence: zhengxin@shao.ac.cn)

Delay (DPD). During the data processing, the first difference between two stations and the second difference
between the phases delay of two satellites are calculated. Because the angular distance between the twosatellites are very close, the DPD eliminates the influence of the atmosphere and ionosphere on the propagation paths of the two satellites’ signals, and the effectof the internal delay of the observation equipment, andit achieves the accuracy of picosecond (ps) order.
Historically, the Apollo Program carried out by
NASA used the same-beam technology. In Japan,
same-beam VLBI observations of the Rstar and Vstar
satellites were carried out in the SELENE mission
in 2008. The calculated DPD was applied to orbit
determination and lunar gravity field model calculation. The orbit determination accuracy of Rstar andVstar reached 10 m and better (Hanada et al., 2010).
In the Chinese Chang’e-3 mission in 2013, DPD ofsame-beam VLBI between Lander and Rover weresuccessfully calculated and used for monitoring theposition of the Rover on the lunar surface, and also
used for relative positioning between Lander andRover (Liu et al., 2014).
During the mission of TDRSS-C4 in May 2018,
TDRSS-C4 and Microsatellite B, which was designed
by Harbin Institute of Technology, separated from therocket and entered the Earth-Moon transfer orbit inturn. In the Earth-Moon transfer section, the two satellites were close enough to meet the requirements ofsame-beam VLBI observations. So while CVN (including BJ, KM, UR, TM) observed TDRSS-C4, atthe same time, the signal of Microsatellite B was also
successfully observed. In this paper, DPD between Microsatellite B and TDRSS-C4 was investigated.
57

58

Zheng et al.

2 Schedule

4.1 DOR signals

The VLBI Center for Deep Space Exploration at
the Shanghai Astronomical Observatory, Chinese
Academy of Sciences (SHAO), received the precise
ephemeris of TDRSS-C4 and Microsatellite B, and thepredicted orbits of these two satellites were calculated
for the observation schedule. Because TDRSS-C4
was the main task of CVN, the accuracy of the
precise ephemeris of TDRSS-C4 was on the order ofseveral hundred meters. The accuracy of the precise
ephemeris of Microsatellite B was far lower than thatof TDRSS-C4.

CVN aimed at TDRSS-C4 and received S-band DOR
signals from the two satellites. The DOR signals fromTDRSS-C4 included one main carrier and two side
tones. The main carrier frequency was 2234 MHz
and the signal-to-noise ratio (SNR) was about 40 dB.
The DOR signal transmitted by Microsatellite B also
contained one main carrier and two side tones. The
main carrier frequency was 2275 MHz, SNR was
about 45 dB, −DOR and +DOR SNR were about
30 dB. The frequency difference between the two main
carriers was 41 MHz.

The schedule which was in the same-beam VLBI
mode used the predicted orbits of the two satellites tocalculate both geometric delay models, and output ajob file for the VLBI correlator. The job file recorded
both geometric delay models of the two satellites andwrote these models in the same format in turn, while
the difference was just the satellite identification.

3 Correlator
The VLBI hardware correlator at SHAO processed theobservation data of the stations according to the job
file, and output data files and tab files with a known
format. Because there were two satellite models in thejob file, correlator outputted two data files and two tab
files with satellite identifications while the same time
tags of both two data files and two tab files. These four
files were what the correlator output in the same-beam
VLBI observation mode.

4 Differential phase delay
The software that calculated differential phase delay
reads the data files and tab files, at the same time reads
the time configuration file which the schedule output
and the correction files which contain the atmosphericand ionospheric delays in the observation direction of
the telescopes. Finally, it outputs the bandwidth synthesis group delay data of these two satellites and DPD
data during the same-beam VLBI observation model isused.

4.2 Correlation phase
One data file and tab file contained cross-correlation
data of which integral time was 0.98304 sec andtotaling 5 cycles. Each integral period could extract six
correlation phases of the main carrier of two satellites.
In this paper, correlation phase of the observed dataon May 22, 2018 was analyzed. Fig. 1(a) shows
six-minutes of the correlation phase of TDRSS-C4
on the BJ-TM baseline. Fig. 1(b) shows the residual
phase after eighth-order polynomial fitting of thecorrelation phase of TDRSS-C4. Fig. 2(a) depicts a
six-minutes correlation phase of Microsatellite B on
the BJ-TM baseline. Fig. 2(b) shows the residual phase
after eighth-order polynomial fitting of the correlation
phase of Microsatellite B. Comparing figs. 1(a) and2(a), 1(b) and 2(b), the correlation phase change rateof TDRSS-C4 was estimated to be −0.5 ps/s, and thatof microsatellite B was about 12 ps/s. The correlation
coefficient of correlation phase between the twosatellites was high, which means that the correlation
phases of two satellites which was extracted from thedata file were correct and the correlation phases for theperiod of 6 minutes had no integer ambiguity.

4.3 Bandwidth synthesis group delay
The bandwidth synthesis group delay includes the geometric delay model of the satellite and the difference between the geometric delay model of the satellite and the actual value. Error contributions such as at-Differential VLBI in Lunar Exploration

59

Fig. 3: Residual of bandwidth synthesis group delay of Mi-

crosatellite B.
Fig. 1: (a) Correlation phases of TDRSS-C4 on BJ-TM baseline

for 6 minutes; (b) Residual phases after an 8th-order polynomial
fitting.

4.4 DPD
Differential group delay (DGD) was obtained by differentiating the group delay of two satellites.
However, the calculation of DPD was relatively
complicated. The main error factors affecting the DPD
were almost cancelled through the subtraction of two
satellites’ phase delay. However, the ionospheric delay was inversely proportional to the square of the frequency. If the signal frequencies of the two satellites
were different, the ionospheric delay must be considered on calculation of the DPD, and an equation tocompute the ionospheric delay is shown in Equation 1.

(τ2ion − τ1ion ) =Fig. 2: (a) Correlation phases of Microsatellite B on BJ-TM

baseline for 6 minutes; (b) Residual phases after an 8th-orderpolynomial fitting.

mospheric delay, ionospheric delay, equipment internaldelay and clock differences need to be corrected. Figure 3 shows the residual of bandwidth synthesis groupdelay against the geometric delay model of Microsatellite B. Judging from Fig. 3, combined with station coordinates, parameters such as predicted orbit and baseline length, the accuracy of Microsatellite B prediction
was thought to be on a level of 20 km.

k × ∆T EC h 1 2
1 i( ) − ( )2
c
f2
f1

(1)

Here, (τ2ion − τ1ion ) is the difference of two satellites’ ionospheric delays. The factor is k = 40.28m3 /s2 .
The expression ∆TEC means the difference of Total
Electron Content in the line-of-sight direction of radio
telescope which could be calculated according to themodel or GNSS (Global Navigation Satellite System)
observation data, and c is the speed of light. Furthermore, f1 , f2 indicate the frequencies of the two satellites signals.
By subtracting the two geometrical delay models
and subtracting the two residual phase delays, and thenadding the two terms, DPD with bias was obtained, as
shown in Equation 2. Because, the offset was a constant bias in a continuous arc, it could be calibrated
during the orbit determination for DPD data spanningfor more than 1 hour.

60

Zheng et al.

Fig. 5: Residuals of DPD after 8-power polynomial fitting.

Fig. 4: DPD which continued more than one hours and could be

used for orbit determination and relative positioning.

τd pd = (τ2geo − τ1geo ) + (

ϕ1
ϕ2
−
)+
2π f2 2π f1

Fig. 6: Residuals of the bandwidth synthesis group delay of Mi-

crosatellite B after orbit determination. Shown are 6 baselines.

(2)(m2 − m1 ) + (τ2ion − τ1ion )Here τd pd was DPD. The terms τ1geo and τ2geo indicate
the geometric delay model of the two satellites. The
terms ϕ1 , ϕ2 show the correlation phases of two satellites, and (m2 − m1 ) indicated the constant bias of DPD
According to the calculation algorithm of DPD, thesoftware calculated DPD between two satellites during TDRSS-C4 and Microsatellite B both in the EarthMoon transfer orbit which in the same-beam VLBI observation model. After analyzing all of DPD data, it
was found that there were more than one hour continuous observations from 14.5 (UTC) to 16 (UTC) on
May 22, 2018. In the whole arc, TDRSS-C4 and Microsatellite B were flying to the Moon in their scheduled orbits. Fig. 4 shows the DPD which observed continuously more than one hour, 6 baselines. Fig. 5 shows
the residual of DPD after fitting by 8th order polynomial, UR-TM baseline. In the next step, these DPD
were used for orbit determination and relative positioning between TDRSS-C4 and Microsatellite B.

5 Orbit determination
Range, range rate and bandwidth synthesis group delay of Microsatellite B on May 22 were used for a firstorbit determination. Since the accuracy of the precise
ephemeris of Microsatellite B was far less than that of
TDRSS-C4, the orbit accuracy of Microsatellite B was
improved to hundreds of meters. Fig. 6 shows the residuals of the bandwidth synthesis group delay of Microsatellite B after orbit determination. Finally, the orbit accuracy of both TDRSS-C4 and Microsatellite B
both reached hundred of meters, and the success rate
was increased by using the same-beam VLBI DPD orbit determination.
After a first orbit determination, the accuracy ofboth satellite orbits reached hundreds of meters. Then,
DPD was applied for the second orbit determination.
Using ranging, range rate and bandwidth synthesis
group delay of both satellites, and DPD that wascalculated by both satellites’ data, the orbits of these
two satellites (TDRSS-c4 and Microsatellite B) were
improved. As shown in Fig. 7, the residual of six
baselines of DPD after orbit determination can becalculated to be 4.97, 5.37, 4.40, 4.87, 2.97, 3.64
ps, respectively. The systematic deviation of the six
baselines is −0.6, −0.675, 0.118, 0.016, 0.43, 0.416 ns.

Differential VLBI in Lunar Exploration

61

these two satellites. The residuals of six baselines canbe calculated to be 4.97 5.37 4.40 4.87 2.97 3.64 ps,
respectively.
Acknowledgements This paper is sponsored by the Natural
Science Foundation of China General Program (11803069,
11803070, 11773060), the Key Laboratory of Planetary Sciences, the Opening Project of Shanghai Key Laboratory ofSpace Navigation and Positioning Techniques, and the Chinese
Lunar Exploration Project. The authors appreciate the support
from the CVN and VLBI center in SHAO.
Fig. 7: The residuals of DPD after orbit determination. Shownare 6 baselines.

References
6 Conclusions
Same-beam VLBI observations between TDRSS-C4
and Microsatellite B were successfully carried out by
CVN during the Earth-to-Moon transfer section in May
2018. We correctly calculated the DPD data and successfully used the DPD data for orbit determination for

Hanada H, Iwata T, Liu Q, et al. (2010) Overview of Differential VLBI Observations of Lunar Orbiters in SELENE for
Precise Orbit Determination and Lunar Gravity Field Study.
Space Science Reviews, 154, 123–144, doi:10.1007/s11214010-9656-9
Liu Q, Zheng X, Huang Y, et al. (2014) Monitoring motion andmeasuring relative position of the Chang’E-3 rover. Radio
Sci., 49, 1080–1086, doi:10.1002/2014RS005449

Comparison of Results Between CVN and K5 Software
Correlators
T. Kondo, W. Zheng, L. Liu, J. Zhang, F. Shu, L. Tong, F. Tong

Abstract CVN (China VLBI Network) software correlator has been developed by SHAO for the lunar
mission. Recently it has been upgraded to a general
correlator to handle the geodetic VLBI observations
data. Observed values, such as delay, delay rate, andfringe amplitude, obtained by CVN software correlator and fringe fitting software “fourfit”have been compared with those obtained by K5 processing system
consisting of software correlatorand fringe fitting software independent from CVN system. As a result, it has
been confirmed that CVN and K5 results show a goodcoincidence.

Keywords CVN correlator · K5 correlator

tween CVN and K5 software correlators. Observed values, such as delay, delay rate, and fringe amplitude, obtained by CVN software correlator and fringe fitting
software ”fourfit” (Cappallo, 2014) have been compared with those obtained by K5 software correlator.
K5 and CVN comparison results show a good coincidence with each other on fine (multi-band) delay, delayrate, and fringe amplitude. The average of the standard
deviation of the differences between X band fine delays
is 7.6 psec. As for the delay rate, the average of differences at X band is 0.00±0.09 ps/s. As for the fringe
amplitude at X band, the average of ratio (CVN/K5)
is 0.98±0.11. K5 correlator is used by GSI (Geospatial
Information Authority of Japan) VLBI group for a routine IVS VLBI data processing, so that CVN correlator has enough performance to process geodetic VLBI
data.

1 Introduction
CVN (China VLBI Network) software correlator developed by SHAO for the lunar mission has been upgraded to a general correlator to handle the geodetic VLBI observations data. K5 software correlator
has been developed by NICT (National Institute ofInformation and Communications Technology, Japan)
VLBI group (Kondo et al., 1999) for processing geodetic VLBI data. We have conducted the comparison beTetsuro Kondo · Weimin Zheng · Lei Liu · Juan Zhang · Fengxian
Tong
Shanghai Astronomical Observatory, 80 Nandan Doad, Shanghai, 200030, China
Tetsuro Kondo also
National Institute of Information and Communications Technology, Japan(Correspondence: kondo@shao.ac.cn)

2 Definition of delay
2.1 Baseline-based processing system
K5 processing system is a baseline-based processing
system. Observed delay is defined as the time required
for the wavefront passing through the reference station(X) at the epoch (PRT: Processing Reference Time) topass through the other station (Y). On the other hand,
as for the earth-centered epoch system like the CVN
system, observed delay is defined as the difference between the time a certain wavefront, that passes throughthe earth center at the epoch, passed through the X station and the time the same wavefront passed throughthe Y station.
62

Comparison of CVN and K5 Correlators߬௫‫ ݐ‬ൌ ‫ݐ‬ଵܺሺ‫ݐ‬ଵሻ‫ ݐ‬ൌ ‫ݐ‬ଶ

߬௫௬ି௕

63

݇

ଵ
ܻሺ‫ݐ‬ଶሻ

߬௫௬߬௫௬ି௕ ߬ሶ ௬߬௬ᇱܻሺ‫ݐ‬ଵ ሻ

߬௬

ଷ

݇

  ଵ
௫௬ି௢
′௫

ଷ
  ଶ
ଶ

௫

’௬

‫ ݐ‬ൌ ‫ݐ‬ଷ
ܱFig. 1: Observed delay in case of baseline-based processing sys-tem. Let t2 be the time when a certain wavefront, that passed
through the X station at t1 (epoch), passes through the Y station.
Observed delay is given as t2 − t1 (= τ xy−b ). O is the center of theearth and k is the wave propagation direction.

In Fig. 1, t2 is the time when a certain wavefront,that passed through the X station at t1 (epoch), passes
through the Y station. Let geometrical delays against
the earth center at t1 be τ x and τy for X and Y stations, and a geometrical delay against the earth centerof Y station at t2 be τ0y . Observed delay is expressedas τ xy−b = t2 − t1 = τ x − τ0y . From the figure, τ0y can begiven as
τ0y = τy + τ xy−b τ˙y(1)where τ̇y is the changing rate of τy at t1 , i.e., delay rate.
Therefore τ xy−b can be written asτ xy−b = τ x − (τy + τ xy−b τ˙y )= τ xy − τ xy−b τ̇y(2)where τ xy = τ x − τy . Solving Eq.(2) for τ xy−b , we getτ xyτ xy−b =1 + τ̇y  ଷ

Fig. 2: Observed delay on a earth-centered epoch system. Ob-

served delay is t3 − t2 = τ0x − τ0y where t2 and t3 are the time a certain wavefront, that passes the earth center at t1 (epoch), passed
through the X station and the time the same wavefront passed
through the Y station.

two times, and t3 is the epoch. Let geometrical delays
against the earth center at t3 be τ x and τy for X andY stations, a geometrical delay against the earth centerfor X station at t1 be τ0x , and a geometrical delay against
the earth center for Y station at t2 be τ0y . Observed delay is expressed as τ xy−o = t2 − t1 = τ0x − τ0y . From thefigure, τ0x can be expressed as
τ0x = τ x − τ0x τ̇ x
where τ̇ x is the changing rate of τ x at t3 (τ˙x < 0 under
the condition illustrated in the figure). Solving for τ0x ,we obtain
τx
1 + τ̇ x; τ x (1 − τ̇ x )

τ0x =

(4)

(∵ |τ̇ x |  1).
Similarly for τ0y , we get

Moreover considering |τ̇y |  1, we finally getτ xy−b = τ xy (1 − τ̇y )

௬

(3)

τ0y = τy (1 − τ̇y ).

(5)Hence observed delay is given as follows.

2.2 Earth-centered epoch processing
systemτ xy−o = τ0x − τ0y= τ x (1 − τ̇ x ) − τy (1 − τ̇y )= τ x − τy − τ x τ̇ x + τy τ̇y .

In case of earth-centered epoch system, observed delay is defined as the difference between the time a certain wavefront, that passes through the earth center atthe epoch, passed through the reference station (X) andthe time the same wavefront passed through the remotestation (Y). In Fig. 2, t1 and t2 correspond to theseUsing relations τ xy = τ x − τy and τ̇ xy = τ̇ x − τ̇y , we getτ xy−o = τ xy (1 − τ̇y ) − τ x τ̇ xy .

(6)

Since τ xy−b is expressed by Eq. (3), τ xy−o can be rewritten as

64

Kondo et al.

3.2 Earth centered epoch correction

Delay
delay change

PRT
PRT

time (UTC)X station clock

Fig. 3: Relation between X-station clock offset and observed de-lay. In case that correlation processing is carried out without correction of clock offset, the epoch (PRT: Processing ReferenceTime) of observed value shifts by the amount of clock offset.
Therefore observed delay at the true PRT can be obtained bycompensating the delay change during the period of the clockoffset.

τ xy−o = τ xy−b − τ x τ̇ xy .

(7)

Namely the correction based on the term “−τ x τ̇ xy ” isnecessary for a comparison between τ xy−b and τ xy−o .
We can get the same correction term, as describedlater, by treating as the shift of the epoch when comparison is made.

3 Observed delay correction
3.1 X-station clock offset
Fig. 3 shows the relation between X-station clock offset and observed delay. In case that correlation processing is carried out without correction of clock offset, theepoch (PRT: Processing Reference Time) of observed
delay shifts by the amount of clock offset. Therefore
observed delay at the true PRT, τtrue , can be obtainedby compensating the delay change during the period ofclock offset. Assuming the clock offset is a very shorttime, we can neglect the higher order terms such as 2nd
and higher of the Taylor’s formula. So that τtrue is givenasτtrue = τobs + xo f f · τ̇ xy(8)where xo f f is the X-station clock offset and τ̇ xy is thedelay rate.

The definition of the epoch is different between thebaseline-based processing system and the earthcentered epoch processing system. It is therefore
necessary to compensate for the difference of theepoch to carry out the comparison of the both observed
delays. In order to match the epoch of the baselinebased processing system to that of the earth-centeredepoch processing system, at first the time of the wavefront, that reaches the center of the Earth at the epoch,passing the X station is computed. Thendelay observedby the baseline-based processing is corrected so as tocompensate this time difference. This compensation
is given by shifting the epoch of the baseline-based
delay by τ0x shown in Fig. 2. Therefore the correction
is given asτobs−o = τobs−b − τ0x · τ̇ xy(9)where τobs−b is the observed delay obtained by thebaseline-based system and τobs−o is that by the earthcentered epoch system. Moreover
τ0x = τ x − τ0x · τ̇ xthen solving for τ0x , we getτ0x = τ x (1 − τ̇ x )(10)

Substituting this to Eq.(9), we getτobs−o = τobs−b − τ x · τ̇ xy + τ x τ̇ x τ̇ xy(11)Absolute values of τ x , τ̇ x , and τ̇ xy on the earth are at
most 0.02sec, 1.5 × 10−6 s/s, and 3 × 10−6 s/s, respectively. Hence maximum value of |τ x τ̇ x τ̇ xy | does not exceed 1 × 10−13 sec(=0.1psec), and the value is smallenough compared with the measurement accuracy ofthe current system. So that this term can be neglected,
then we getτobs−o = τobs−b − τ x · τ̇ xy .
This is the same as Eq. (7).

(12)

Comparison of CVN and K5 Correlators

65

Fig. 4: Result of the comparison of fine delay (multi-band delay)

Fig. 5: Result of the comparison of fine delay (multi-band de-at X band. An alphabetical symbol means a radio source. No correction is applied to K5 results. Standard deviation of differences
reaches a large value of 20 nsec at the SESHAN25-WETTZELL
baseline.

lay) at X band. The latest version is used for K5 processing, i.e.,
X-station clock offset is compensated during a correlation processing. Earth-centered epoch correction is applied to these K5
results. χ2 is less than 1 for most of the baselines. This means
the difference is less than the theoretical error caused by thermal
noises, i.e., K5 and CVN results show a good coincidence.

3.3 Summary of corrections
Corrections for observed delays obtained by K5 system
can be summarized as follows.
τobs−o = τobs−b + (xo f f − τ x )τ̇ xy(13)

By differentiating Eq. (13) with respect to time, we get
the relation regarding observed delay rates as follows.
τ̇obs−o = τ̇obs−b − τ̇ x τ̇ xy + (xo f f − τ x )τ̈ xy(14)

where theoretical values of τ x , τ̇ x , τ̇ xy , and τ̈ xy are used
for an actual calculation.

4 Results of comparison
As for comparison studies, we use the VLBI experiment data conducted on 2014/349 07h-08h UT.
Four stations, such as NYALES20, SESHAN25,TSUKUB32, and WETTZELL, were participated in
the experiment.
As for K5 processing system, the latest version thatcompensates X clock offset during a correlation processing is used, therefore the correction of X clock offset is unnecessary in the comparisons.
Fig. 4 shows the result of the comparison of finedelay (multi-band delay) at X band. No correction isapplied to K5 results. Standard deviation of differences

Fig. 6: Result of the comparison of delay rate at X band. The lat-est version is used for K5 processing, i.e., X-station clock offset
is compensated during a correlation processing. Earth-centeredepoch correction is applied to K5 results. K5 and CVN results
well coincide with each other, and the average of difference is
0.00 ± 0.09 ps/s.

is about 1.2 nsec at the SESHAN25-TSUKUB32 baseline, but it reaches a large value of 20 nsec at the
SESHAN25-WETTZELL baseline.
Fig. 5 shows the same as Fig. 4, but the earthcentered epoch correction is applied to K5 results.
Standard deviation of differences ranges from 4.9 psec
to 11.1 psec. χ2 is less than 1 for most of the baselines.
This means the difference is less than the theoretical error based on thermal noises, i.e., K5 and CVN results
show a good coincidence.

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Kondo et al.

Fig. 7: Result of the comparison of fringe amplitude at X band.

Both amplitudes well coincide with each other. The average of
CVN/K5 is 1.05 ± 0.16.

Fig. 6 shows the result of the comparison of delay
rate at X band. K5 and CVN results well coincide witheach other, and the average of difference is 0.00 ± 0.09
ps/s.
Fig. 7 shows the result of the comparison of fringe
amplitude at X band. Both amplitudes well coincidewith each other. The average of CVN/K5 is 1.05±0.16.
All results for X band are summarized in Table 1.
Table 1: Summary of comparison between K5 and CVN

mean
σFine Delay (K5-CVN) (psec)
Ts-Wz Ny-Wz Ny-Sh Ny-Ts Sh-Ts Sh-Wz mean
97.7 75.7 -285.0 -26.3 257.2 357.8 79.5
4.9
8.4
7.9
7.4
5.7 11.1
7.6

mean
σ

Delay Rate (K5-CVN) (ps/s)
Ts-Wz Ny-Wz Ny-Sh Ny-Ts Sh-Ts Sh-Wz mean
-0.010 -0.011 -0.042 0.025 0.003 0.017 -0.003
0.050 0.110 0.136 0.171 0.047 0.048 0.094

Amplitude Ratio (CVN/K5)
Ts-Wz Ny-Wz Ny-Sh Ny-Ts Sh-Ts Sh-Wz mean
CVN/K5 1.03 0.97 0.97 1.04 0.90 0.98 0.98
σ0.12 0.01 0.16 0.08 0.10 0.16 0.11
Station ID: Ts(TSUKUB32), Wz(WETTZELL),
Ny(NYALES20), Sh(SESHAN25)

5 Conclusion
Results obtained by CVN software correlator havebeen compared with those obtained by K5 software

correlator. Earth-centered epoch correction and X
clock offset correction are applied to K5 results. As aresult, K5 and CVN results shows a good coincidencewith each other on observed values, such as, fine(multi-band) delay, delay rate, and fringe amplitude.
The average of the standard deviation of the differences between X band fine delays is 7.6 psec. As forthe delay rate, the average of differences at X band is
0.00 ± 0.09 ps/s. As for the fringe amplitude at X band,the average of ratio (CVN/K5) is 0.98 ± 0.11. Offsets
seen in delay is thought to be due to the differenceof fringe fit algorithm that can be influenced by an
instrumental delay (phase structure in a channel andband). However, they do not affect geodetic results,
because these offsets can be treated as a clock offset ata baseline analysis.
Acknowledgements A part of this work has been funded by
Chinese Academy of Sciences (CAS) President’s International
Fellowship Initiative, Grant No. 2018VEA00017.

References
Cappallo R (2014) Correlating and fringe-fitting broadband
VGOS data. In: D. Behrend, K. D. Baver, K. L. Armstrong:
IVS 2014 General Meeting Proceedings, Science Press (Beijing), 91–96
Kondo T, Sekido M, Kiuchi H (1999) KSP bandwidth synthesizing software. J. Commun. Res. Lab, 66(1), 67–76

Status of the Future RAEGE Radio Telescope at Gran Canaria
D. Cordobés, V. Araña, J. A. López Pérez, A. Garcı́a, I. Domı́nguez Cerdeña, J. Ticay, P. Dorta, I. Pérez,
J. A. López Fernández, J. Gómez González

Abstract The IGN in cooperation with the Azores
Regional Government, is developing since 2012 theRAEGE network, which consists of four VGOS
antennas for space geodetic observation. Currently,
two of the four antennas are operative at Santa Maria(Azores) and Yebes (Guadalajara, Spain). The third
antenna will be operational by 2021 at Gran Canaria(Spain) with the cooperation of the University of
Las Palmas de Gran Canaria (IDeTIC-ULPGC). We
present here the progress made on the site selection,
construction and a snapshot of the future projects for
the VLBI antenna of Gran Canaria.
The site was selected after a longterm noise measurement all along the island. The chosen final site isclose to Artenara village at an altitude of 1100 m andpresents the lowest measured electromagnetic noise.
At the present time, we have finished the bureaucratic
procedures with local administrations and almost
finished the architecture projects for the different
buildings of the site.
The Artenara station will have a fully compliant
VGOS radio telescope, equipped with a broadband
receiver in the 2 − 14 GHz band. In addition to these,
the facilities at Artenara will also include an absolutegravimeter, a GNSS receiver and a seismic station,with the goal of turning Artenara RAEGE site into a
Geodetic Fundamental Station.

Keywords VGOS · RAEGE · Gran Canaria

1 Introduction
The RAEGE (Red Atlántica de Estaciones
Geodinámicas Espaciales) project results from a
Memorandum of Understanding between the Spanish
National Geographic Institute (IGN, Ministerio de
Fomento, Gobierno de España) and the Governmentof the Portuguese Autonomous Region of Azores(Secretaria Regional da Ciência, Tecnologia e Equipamentos, Governo dos Açores), signed in 2011, to meetthe international developments needed to set up a
VLBI (Very Long Baseline Interferometry) Geodetic
Observing System - VGOS.

David Cordobés · José Antonio López Pérez · Abel Garcı́a ·Itahiza Domı́nguez Cerdeña · José Antonio López Fernández ·Jesus Gómez González
Instituto Geográfico Nacional
C/General Ibañez de Ibero, Madrid, SpainVı́ctor Araña · Jaime Ticay · Pablo Dorta · Iván Pérez
Instituto para el Desarrollo Tecnológico y la Innovación en Comunicaciones (IDeTIC), Universidad de Las Palmas de Gran Canaria (ULPGC), Spain(Correspondence: d.cordobes@oan.es)

Fig. 1: The RAEGE radio telescope in Yebes (Spain).

67

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Cordobés et al.

Fig. 2: Site location at Gran Canaria and zoom to the Artenara municipality.

The project consists of a network of four fully
equipped Geodetic Fundamental Stations in Spain(Yebes, Guadalajara and Gran Canaria, Canary Islands), and Azores, Portugal (Santa Maria and Flores
islands) and two Base Centres (Yebes/Spain and
Lagoa-São Miguel/Azores), dedicated to astronomy,
geodesy and geophysics studies.
The basic equipment of all RAEGE’s Geodetic
Fundamental Stations is:• VGOS radio telescope (13.2 m diameter; operation
up to 90 GHz; Fast slewing speed)• Gravimeter• Permanent GNSS station• Maser clock• Seismic station

2 The radio telescope
The construction of the radio telescope started at theend of 2010 when the contract for the design, construction, and commissioning of the first three radio telescopes was awarded to MT Mechatronics (Germany).
The design of the radio telescopes was completed in
the summer of 2011. During 2011 and 2012 the backstructures of the three radio telescopes were built byAsturfeito in Asturias, Spain. Other parts, such as thereflector panels, were fabricated by COSPAL Composites in Italy. The RAEGE radio telescopes are Az-

imuth/Elevation turning head telescopes, reaching azimuth and elevation slew speeds of 12o /s and 6o /s, respectively. The optical design is based on a 13.2 m ringfocus reflector. In its basic configuration, the observation frequency is in the range of 2 − 40 GHz. It can beenhanced up to 100 GHz by using additional options.
For geodetic telescopes it is essential to be able to accurately measure the position of the intersection of the azimuth and elevation axes. Therefore a concrete pillar is
installed at the center of the telescope tower, allowing
the installation of a measurement system to be locatedat the intersection of axes and visible from the outside
through openings. Another important requirement in
geodetic VLBI is path length stability. In order to handle path length errors, an active deformation measurement and “flexible body compensation” (FBC) method
is foreseen, similar to established methods used for surface and focus/pointing error corrections.
The specifications of the radio telescope are:
• Max. azimuth, elevation speed: 12o /s , 6o /s• Acceleration: 3o /s2• Frequency operation range: up to 40 GHz• Path length error < 0.26 mm• Elevation, azimuth movement range: 0 − 100o , 0 −540o• Pointing accuracy < 16 arcsec• Power consumption < 170 kW• Aperture efficiency > 60 % at 8 GHz (using VGOS
receiver).

Status of RAEGE Gran Canaria

Fig. 3: Blueprint of the future RAEGE station and two photographs of the site before any construction

Fig. 4: Artistic reproduction of the future radio telescope.

69

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Cordobés et al.

• High altitude (1100 m a.s.l) to avoid clouds during
longest periods of the year
• Low humidity• Public owned terrain that can be transferred to the
IGN• Electrical infrastructure available• Geological stability. The site is located close to
Artenara village on old ignimbrite rocks with various million years. Most recent volcanic activity is
far from the site and the probability of a future volcanic eruption on the island is of lower than 1 % for
the next 100 years.

Fig. 5: Site testing map of most promising sites.

The RAEGE Gran Canaria site was chosen after an intensive RFI measurement campaign around the island.
At the center of Gran Canaria there are some militar
and meteorological radars whose electromagnetic radiation covers most of the island so it was hard to finda suitable place with low RFI levels. Eventually Artenara was chosen as it is shadowed by a nearby mountain from the radar, and as it is in the border of a naturalpark, the electromagnetic pollution is guaranteed to remain the lowest possible for the future years.

4 Status and future work

Fig. 6: RFI measurement for the selected site.

3 Site selection
Several factors were considered for the selection of the
RAEGE Gran Canaria site:• Low RFI in order to maximize the observing frequency band of the radio telescope

Currently, the radio telescope is kept inside containers
in a warehouse of Gran Canaria island and we are waiting for the bureaucratic permissions to start the civil
works at the site. If everything goes well, we expect tobegin the works by the end of 2019. The first stage willbe the conditioning of the terrain and the constructionof the interior roads. In a second stage, the radio telescope will be built. In the final stage, which will be by2021, the control building will be made, and the station
will be operative. We hope to achieve the first fringes
during 2022.

First Steps in Gravitational Deformation Modelling of the VLBI
Yebes Radio Telescopes
A. Prudencio, E. Azcue, J. López Ramasco, S. Garcia-Espada, Y. Gómez Espada, V. Puente, M. Valdés

Abstract In this work, the first steps in the gravitational deformation modelling of the VLBI antennas ofYebes by using terrestrial laser scanner are presented.
A preliminary simulation of the measurements and its
processing in Matlab and the future work and campaigns are shown.

Keywords Gravitational deformation
trial Laser Scanner · VLBI·

Terres-

The effect of gravity in VLBI antennas is one ofthese errors that should be taken into account in theanalysis of VLBI data. This effect can reach several
millimeters and it has to be determined specifically foreach radio telescope (Sarti et al., 2009).
The National Geographic Institute of Spain (IGN)
works to achieve the optimal operation in their stations.
This includes the determination of this effect. In thiswork the first steps to the antenna gravitational deformation modelling and the tools developed for the dataprocessing are shown.

1 Introduction
2 GoalGeodetic VLBI is one of the most accurate geodetic
techniques for the study of the size and shape of the
Earth, its rotation and time variations. This accuracy isachieved taking into account all the error sources involved in the process.
Andrea Prudencio
Department Section of Astronomy and Geodesy, Faculty ofMathematics, University Complutense of Madrid, ES-28040
Madrid, Spain
Esther Azcue · Yaiza Gómez Espada · Vı́ctor Puente ·Marcelino ValdésInstituto Geográfico Nacional
C/General Ibañez de Ibero, Madrid, Spain
J. López Ramasco
Observatory of Yebes - Instituto Geográfico Nacional
Cerro de la Palera S/N Yebes, Spain
Susana Garcia-Espada
Instituto Geográfico Nacional - RAEGE Santa Maria station,
Azores, Portugal(Correspondence: anpruden@ucm.es)

The aim of this work is to present the first steps ingravitational deformation modelling of the Yebes radio
telescopes. At the end of 2018, the IGN acquired a Terrestrial Laser Scanner (LS) that will be used to measure
the gravitational deformation at different elevations of
the IGN telescopes. Before the campaign planning, apreliminary study of this effect has been made. The objective was to start developing some tools that could
be useful to plan the campaign and to model the LS
cloud in the future. Four Matlab routines were developed with the next objectives:• To study and analyse the gravitational influenceson large VLBI telescopes. Simulation of a LS measurements affected by structure’s self weight andwhite noise.
• To determine the best fit paraboloid to the point
cloud simulated and to estimate the deformation
parameters (3 translations, 2 rotations and focal
length variation).
71

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Prudencio et al.

• To compare the best fit paraboloid obtained withthe original data.

3.4 Best-fit paraboloid estimation• To contrast the gravitational deformations at different telescope elevations and to plot these differences.

A Matlab function for studying the relative deformations of the dish at different elevation angles was programmed. An interpolation between clouds to a common grid is done for evaluating the differences in thatpoints. Also a summary of the best-fit paraboloid parameters in each angle is done, see Fig. 4.

3 Routines
3.1 Gravitational deformation
simulation
A simulation of deformations in a generic antenna wasmade by using the Finite Element Method (FEM).
It was considered in the model that the deformation
caused by the structure’s self weight is proportional
to the square of the height (Cheng, 2009) and someboundary conditions were taking into account. This deformed dish together with white noise added simulate
the measurements of a LS and it will be used in thenext routines as a test point cloud. Several point clouddensities and sigma for the white noise can be selected,
see Fig. 1.

3.2 Best-fit paraboloid estimation
In order to associate the model to a best-fit paraboloid,a Matlab function was written. A least-squares adjustment is computed to estimate six parameters: threetranslations to transform the origin of the model in thevertex of the paraboloid, two rotations to solve any misalignment between them and the focal length variation,
see Fig. 2.

3.3 Best-fit paraboloid comparison
A Matlab function was programmed for doing acomparison between the point cloud and the best fit
paraboloid. This function generates a plot output andsome statistics of the adjustment, see Fig. 3.

4 Conclusions and future plans
Comparing the model to different bibliography (Sarti
et al., 2009; Artz et al., 2014) these programs seem towork correctly. In the light of these results, it is expected to use these routines with the real data measurements of the scanner that will be used to determine gravitational influences on Yebes antennas. Future plans:
1. To improve the simulation function incorporating
more information of the antenna’s structure. Currently a very simple and generic model was usedbecause its primary aim was only to simulate themeasurements of the laser for developing the restof the programs.
2. To plan and carry out the survey in the Yebes antennas with the laser scanner over the next months.
3. To contrast these results with the model obtainedwith the laser scanner data.

References
Artz T, Springer A, Nothnagel A (2014) A complete VLBI delay
model for deforming radio telescopes: the Effelsberg case.
J Geod, 88, 1145–1161, doi:10.1007/s00190-014-0749-1
Cheng J (2009) The Principles of Astronomical Telescope Design. Springer, 634 p.
Clark T A, Thomsen P (1988) Deformations in VLBI Antennas
NASA TM-100696, 96 p.
Sarti P, Vittuari L, Abbondanza C (2009)
Laser Scanner and Terrestrial Surveying Applied to Gravitational
Deformation Monitoring of Large VLBI Telescopes‘
Primary Reflector.
J Surv Eng, 135(4):136–148,
doi::10.1061/(ASCE)SU.1943-5428.0000008

Gravitational Deformation of Yebes Telescopes

90º

75º

60º

73

45º

30º

15º

0º

Fig. 1: Simulation of the deformations of the dish at different elevations in 3 and 2 dimensions (along the elevation axis). A 40 m

antenna and 15 m focal length was considered, similar to the Yebes antenna. Deformations in meters.

Fig. 2: Focal length variations estimated for the 40 m antenna simulated in different elevations. In red the estimated values, in blue

the 2nd order polynomial adjusted.

74

Prudencio et al.

Fig. 3: Transect of the deformed model and the best-fit paraboloid along the elevation axis at 30 degrees elevation.

Fig. 4: Relative deformations of the dish between the model at 30o and the one at 90o . Units: X and Y axis in meters, deformations

in millimeters.

The Onsala Tide Gauge Station: Experiences From the First
Four Years of Operation
G. Elgered, J. Wahlbom, L. Wennerbäck, L. Pettersson, R. Haas

Abstract A tide gauge station was installed at the Onsala Space Observatory in 2015. The official tide gauge
station includes several independent senors: one radarand three pneumatic sensors (also referred to as bubblers). The radar and two bubblers are mounted in awell and one bubbler outside the well. Additional sensors such as one laser sensor and three radar sensors
have been used during different time periods in order tofurther assess the quality of the acquired sea level data.
Here we compare the four official sensors and the laser
sensor which was installed in April 2016. The expected
accuracy (one standard deviation) for all of these sensors is approximately 3 mm, according to the datasheet specifications. Results from the first four years ofoperations are used to assess and estimate the actual accuracies by means of comparisons between the sensors.
We observe typical biases over time scales of monthsof up to 10 mm. Biases are caused by uncertainties of
the reference level of the sensor, the density of the water for the bubblers, multipath effects for the radar, andnonlinearities with temperature for the laser. The observed monthly standard deviation between the sensors
in the well vary between 2 mm and 6 mm, which isroughly consistent with the data sheet specifications.

Keywords Sea level · Tide gauge station
Gunnar Elgered · Lars Wennerbäck · Lars Pettersson · Rüdiger Haas
Chalmers University of Technology, Onsala Space Observatory,
SE-439 92 Onsala, Sweden
Jonas Wahlbom
App-pharm Sweden AB, Skalkarike, Hästängen 2, SE-541 96
Väring, Sweden(Correspondence: gunnar.elgered@chalmers.se)

Fig. 1: The tide gauge station at the Onsala Space Observatory.

1 Introduction
The location of the Onsala geodetic VLBI telescopes
close to the coast line motivates continuous and accurate sea level observations, especially given the recent finding of an accelerating global sea level rise
(Nerem et al., 2018). A tide gauge station (Fig. 1) was
developed and constructed in house, with advise fromthe Swedish Meteorological and Hydrological Institute(SMHI). Since the end of June 2015 it is an official
site in SMHI’s national monitoring network of the sea
level.
In Section 2 we describe the individual sensors.
In Section 4 we present the sea level observations acquired so far, and in Section 4 we summarise the levelling carried out in order to connect the sea level data
to the reference markers at the observatory. Finally, theconclusions are given in Section 5.

2 Sea level sensors
The official tide gauge station has several independent
sensors: one radar (Fig. 2) and three pneumatic sensors
75

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Elgered et al.

sensors (bubblers) are offered with different accuracy.
The type used are by the manufacturer Ott referred to
be of USGS type (possibly because they fulfil requests
from the United States Geological Survey). The threepneumatic sensors are in the following referred to as
USGS1, USGS2, and USGS3. The bubbler USGS3,
originally mounted outside the well, was taken out of
operation on 17 April, 2019. This sensor is discussed
further in the next section.
The laser sensor was installed 29 April 2016
(Börjesson et al., 2016). A reflector is floating in apipe and its surface is above the actual sea level.
The reflector used up to 13 September 2017 was
9 mm above the sea level. Thereafter, a new improved
reflector was installed. Its reflecting surface is 11 mmabove the sea level. These corrections have been taken
into account when presenting the results. For moredetails about the laser, see Micro-Epsilon (2016).
The VEGA61 radar is similar to the sensors used in
the Swedish observational network operated by SMHI.
Fig. 2: The down-looking radar sensor, Campbell CS476, operating at 26 GHz, mounted at the top in the centre of the well.

Fig. 3: The pneumatic sensors, Ott CS471 of USGS type, havea compressor (green unit, left) located in the measurement hut.
Each compressor is connected to a nozzle (right) via a plastic
pipe. Two nozzles are used at the bottom of the well, and one
nozzle is located close to the bottom outside of the well. The
original black nozzles corroded rapidly in the salty water andwere replaced by the ones located just above (manufactured incopper) in October 2016 (see also Fig. 5).

(Fig. 3, also called bubblers). Now in July 2019 there
are also one laser (Fig. 4) and two more radar sensors
installed in the well for quality assessment of the official data (Fig. 5).
The Campbell CS476 radar is our main sensor andis in the following referred to as CS476. The pneumaticFig. 4: The laser sensor is mounted on the inside wall of the well.
A reflecting target is floating on the sea surface inside the pipe.

Onsala Tide Gauge Station

77

Fig. 6: The sensors in the well. The plastic tubes to the bubbler

sensors goes into the water to the left just outside of the photo.
The photo is taken on 23 August 2018.
Fig. 5: Design of the tide gauge well. The official sensors are

the Campbell radar CS476, mounted at the top in the centre andthe three USGS bubblers. The pink circles denote temperature
sensors, for the air and the water inside the well (T1 and T2)
and outside of the well (T3 ad T4), and in the insulation layerof the well (T5–T7). The inner diameter of the well is 1.4 m.
The insulation in the walls is 30 cm and the thickness of theouter concrete rings is 15 cm, resulting in an outer diameter ofthe well of 2.3 m.

The radar signal is propagating in a vertically mounted
circular waveguide. It has been acquiring data since
1 December 2016.

Finally, it shall be mentioned that an additional
tide gauge station is operated at the observatory using GNSS technology. It has been acquiring data since2011. This station is primarily used to investigate different analysis methods in the processing of GNSS data
and the results are for example compared to the official
station presented in this paper. For more details on the
GNSS tide gauge station and its results, see Löfgren
et al. (2014); Löfgren and Haas (2014); Hobiger et al.
(2014); Strandberg et al. (2016, 2017, 2019).

The VEGA64 radar was installed more recently
in order to investigate any possible differences due
to multipath effects compared to the main sensor, theCS476 radar. The VEGA64 radar is operating in ahigher frequency range, 76–80 GHz. It has a lens hornantenna which implies a more narrow beam angle.
The full width half power beam width is 3.0° comparedto the CS476 that has an 8° beam angle. It has acquired
data from 14 September 2018.
The sketch shown in Fig. 5 gives an overall impression of the design and the approximate locations of thesensors and Fig. 6 depicts the present setup of sensors
in the well. In the next section we compare the four
official sensors and the laser sensor.

Fig. 7: The official time series, based on the CS476 radar sensor,

is available from the SMHI web page. The sea level variationsat Onsala are mainly caused by weather, and not by tides. The
highest sea level measured so far, approximately +1.5 m, wasduring the storm Urd in December 2016.

78

Elgered et al.

3 Observational results
The official time series, based on the CS476 radar
sensor, from the start in June 2015 until the end ofJune 2019 is shown in Fig. 7. Using these four yearsof data we estimate a linear trend of −1.4 cm/year(the red line in Fig. 7). The expected long term trend
should be close to zero, because both the land uplift
as well as the global sea level have been estimated tobe slightly above 3 mm/year (BKG, 2018; Nerem etal., 2018). The negative value obtained for this time series is mainly due to the low sea levels observed during
the first half of 2018. This illustrates the need for stable long time series of observations in order to assess
any changes in climate related parameters. The international standard averaging period to calculate a single data point when monitoring a climate parameter is
30 years. This was decided at a meeting in Warsaw in1935, at which the directors of most national meteorological institutes took part (Førland et al., 1992).
An example of sea level observations with the radar
CS476 and the laser showing the short term variations
during the month of December 2018 is presented inFig. 8. The corresponding differences are shown in
Fig. 9. For this month the bias (radar − laser) is 3.8 mm
and the standard deviation of the differences is 4.3 mm.
Monthly biases and SDs between the radar and fourother sensors have been calculated from samples withthe temporal resolution of 1 min and are summarisedin Table 1.
Table 1: Monthly biases and standard deviations between theradar sensor and the other sensors
Radar CS476 Monthly bias Monthly standard deviation
vs.
(mm)
(mm)
Laser
3– 4
2– 5
USGS1
1 – 10
2– 5
USGS2
1– 9
2– 6
USGS3
6 – 142 – 14

Biases are caused by uncertainties of the reference
level of the sensors, plus the salinity and temperature
determining the density of the water for the USGS bubblers, multipath effects for the radar, and an uncertaintyof the reference level of the floating reflector for thelaser. In terms of their monthly biases it is clear thatthe laser and radar show superior stability compared tothe bubblers.

Fig. 8: Sea level observations at Onsala during December 2018.

Fig. 9: Time series of the difference between the CS476 radarand the laser sensor.

The USGS3 bubbler, mounted outside the well is
expected to show a larger variability given that the wellacts as a low-pass filter. However, we have noted, apartfrom just looking at the SDs, that a systematic negative bias sporadically occurs, compared to the othersensors. We have no obvious explanation for this behaviour and as mentioned above the sensor has beentaken out of operation on 17 April, 2019.

4 Vertical control
Given the importance of monitoring the sea level withthe highest possible accuracy, levelling of reference
markers has been carried out (at least) annually. Fig. 10
depicts the area close to the tide gauge station including the reference markers. In order to illustrate thestability of the tide gauge station the levelling resultsof the reference marker 827d are summarised in Table 2. This marker is the one most easily accessible,
and is therefore the most frequently measured, of themarkers located inside the well. We note that the standard deviation of these levelling results is 0.3 mm.
The most recent levelling results were documented by
Heep (2018).

Onsala Tide Gauge Station

79

References

Fig. 10: Sketch of the area around the tide gauge station. Mark-ers 820, 821, and 822 are steel markers mounted in the bedrock.
Marker 826 is on the pipe protecting the plastic tube to the nozzle
of an old bubbler, taken out of operation in June 2015, markers
827a, b, c, and d are on the upper side of the mount for sensors
in the well, and marker 828 is on the bubbler outside the well.
Table 2: The levelling results of reference marker 827d

Date

RH2000 vertical coordinate of 827d(m)
2015-08-13
2.4875
2016-08-05
2.48682017-06-01
2.48712017-07-26
2.48742017-08-11
2.4872
2018-08-23
2.48755 Conclusions and outlook
We find that the different sensors roughly perform according to their specifications. The radar and the laser
sensors appear to be more stable in terms of long term
systematic errors. Therefore, future work will focus on
these two sensors, plus the additional two radar sensors
installed in the well. A possible development may bethat the present primary sensor, the CS476 radar, is replaced by the high frequency VEGA64 radar. However,in order to take such a decision, extensive comparisons
between the laser and the different radar sensors mustfirst be carried out.

Bundesamt für Kartographie und Geodäsie (BKG) (2018)“VTRF Station Positions & Velocities”,
http://www.ccivs.bkg.bund.de/EN/Quarterly/VTRF-Results/
VTRF-Stations/vtrf-stations node.html, last access: 15 Nov.
2018.
Börjesson E, Jansson J, von Rosen Johansson C (2016) Test
och implementering av en laserbaserad havsnivåmätare (inSwedish), Bachelor Thesis, Dep. of Earth and Space Sciences, Chalmers Univ. of Tech.
Førland E J, Hanssen-Bauer I, Nordli P Ø (1992) New
Norwegian climate normals—but has the climatechanged?
Norwegian J. Geography, 46, 83–94,
doi::10.1080/00291959208552287
Heep N (2018) Erweiterung des terrestrischen Kontrollnetzes der Twin-Teleskope an der Fundamentalstation Onsala.
Bachelor-Thesis, Frankfurt Univ, of Applied Sci., Matrikelnummer 1138382.
Hobiger T, Haas R, Löfgren J (2014) GLONASS-R: GNSS
reflectometry with a Frequency Division Multiple Accessbased satellite navigation system. Radio Sci., 49(4), 271–
282, doi:10.1002/2013RS005359
Löfgren J, Haas R, Scherneck H-G (2014) Sea level time series
and ocean tide analysis from multipath signals at five GPS
sites in different parts of the world. J Geodyn, 80, 66–80,
doi:10.1016/j.jog.2014.02.012
Löfgren J, Haas R (2014) Sea level measurements using multifrequency GPS and GLONASS observations. EURASIP
J. Adv. in Signal Proc., 2014:50, doi:10.1186/1687-61802014-50
Micro-Epsilon, Instruction Manual optoNCDT ILR 1181 / 1182,
Micro-Epsilon Messtechnik GmbH & Co. KG, Königbacher Str. 15, 94496 Ortenburg, Germany, http://www.
micro-epsilon.se, last access: 21 Sep. 2016.
Nerem R S, Beckley B D, Fasullo J T, et al. (2018)
Climate-change—driven accelerated sea-level rise detected in the altimeter era.
PNAS, 115(9), 122–125,
doi:10.1073/pnas.1717312115.
Strandberg J, Hobiger T, Haas R (2016) Improving GNSS-R sea
level determination through inverse modeling of SNR data.
Radio Sci., 51, 1286–1296, doi:10.1002/2016RS006057
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Ground-Based GNSS-R. IEEE GRSL, 14(9), 1552–1556,
doi:10.1109/LGRS.2017.2722041
Strandberg J, Hobiger T, Haas R (2019) Real-time sea-levelmonitoring using Kalman filtering of GNSS-R data. GPS
Solutions, 23:61, doi:10.1007/s10291-019-0851-1

VLBI-GNSS Collocation Survey at the Ishioka VLBI Station
H. Munekane, M. Umei, H. Ueshiba, S. Matsumoto, T. Wakasugi, S. Kurihara

Abstract We conducted a collocation survey campaign
in November 2018 to determine a local tie vector between the Ishioka VLBI station and the IGS station
ISHI. In order to estimate the VLBI antenna invariant
point (IVP), the azimuth and elevation axes were estimated from trajectories of targets installed inside theantenna cabin. The offset between the azimuth and elevation axes was ∼ 0.2 mm and the error in the orthogonality of the axes was sufficiently small. Finally, we
determined the coordinate of the IVP as the intersection of the axes, and precisely estimated the local tie
vector between the Ishioka VLBI station and the IGS
station ISHI.

Keywords Local tie vector · VLBI · GNSS

1 Introduction
The International Terrestrial Reference Frame (ITRF)
is constructed by a combination of different setsof station coordinates provided by the four space
geodetic techniques; Doppler Orbitography by Radiopositioning Integrated by Satellite (DORIS), Global
Navigation Satellite System (GNSS), Satellite Laser
Ranging (SLR), and Very Long Baseline Interferometry (VLBI). In order to achieve this combination,
it is necessary to have relative positions, or local tie
Hiroshi Munekane · Michiko Umei · Haruka Ueshiba · Takahiro
Wakasugi · Shinobu Kurihara
Geospatial Information Authority of Japan, 1 Kitasato, Tsukuba
city, 305-0811 Japan(Correspondence: munekane-h96nu@mlit.go.jp)

vectors, between instruments at a collocation sitewhich has multiple space geodetic techniques.
The Geospatial Information Authority of Japan(GSI) started the construction of the Ishioka geodetic
station in 2011. The Ishioka geodetic station has two
space geodetic instruments; VLBI and GNSS. The
VLBI observation system at the Ishioka geodetic
station (Ishimoto et al., 2016) is designed for the
next-generation VLBI system called VGOS, which
is promoted by the International VLBI service forGeodesy and Astrometry (IVS) . The constructionof the VLBI antenna was completed in March 2014,
and the station has participated in the international
observations since 2015. The GNSS station ISHI
has been in operation since 2014, and added to theInternational GNSS Service (IGS) network in 2018.
The GSI has so far performed VLBI-GNSS collocation surveys at Tsukuba, Shintotsukawa, Aira, andChichijima station in Japan (Matsuzaka et al., 2002)
and contributed to the construction of ITRF. We conducted the collocation survey at the Ishioka geodetic
station in November 2018 in order to provide the local
tie vector for forthcoming ITRF 2020.

2 Observations
Fig. 1 shows a panoramic view of the Ishioka geodetic station. Four pillars and a VLBI ground marker are
installed in the station. The collocation survey was performed using these pillars and the VLBI ground marker
for determining the local tie vector between the VLBI
antenna invariant point (IVP) and the reference point of
the IGS station ISHI. The survey was performed from80Collocation Survey at Ishioka

81each pillar to the point closest to it on the bottom of thechoke ring antenna, and then calculated the distancefrom the pillars to the ARP using the design value ofthe antenna. In addition, regarding the height of ARP,
we measured the height of a point on the bottom of theantenna with respect to pillars by the leveling surveys,
which may be considered as the height of the ARP.

Fig. 1: Panoramic view of the Ishioka geodetic station. Four pil-lars and a VLBI ground marker are arranged around the VLBI
telescope. The IGS station ISHI is installed about 40 m awayfrom the VLBI telescope. ISK2 is also installed as an auxiliary
for ISHI.

8th to 22nd November 2018. The details of the survey
will be described in the following sections.

2.1 Surveys among pillars/VLBI groundmarkerWe measured the horizontal angles, vertical angles
and spatial distances among the pillars and the VLBI
ground marker by a Total Station (TS). Then we
carried out leveling surveys between pillars or the
VLBI ground maker to determine relative heights. In
addition, we conducted GNSS surveys at the pillars 2
and 3, and at a nearby mountain, Mt. Tsukuba in order
to measure the orientation angle of the local frame sothat one may express the survey results in a geocentricreference frame.

2.3 Determination of the VLBI antenna
invariant point (IVP)The IVP of the VLBI antenna is defined as the intersection of the azimuth and elevation axes. Its position
should be determined indirectly since it is not directly
observable. For that purpose, we first installed the targets on the cabin wall. Then we observed the targets
from a TS installed on cabin base, which does not follow the antenna movement (Fig. 2).
We first carried out measurements for determining the azimuth axis. We set the antenna elevation tozero, and observed four targets while changing the antenna azimuth by 30 degree from 0 to 330 degree (leftin Fig. 3). Then we carried out measurements for determining the elevation axes. In order to investigate
the dependency of the estimated elevation axes on azimuthal direction, we tentatively estimated the elevation axes at the azimuth of 125 degree and 215 degree. For each antenna azimuth, we observed two targets while changing the antenna elevation by 10 degreefrom 0 to 90 degree (right in Fig. 3). In total, we obtained 48 target positions for the determination of theazimuth axis and 40 target positions for the determination of the elevation axes. Finally, we carried out TS
observations from the TS on the cabin base to the surrounding pillars to determine the positions of the TS.

2.2 Surveys between pillars and IGS
station3 Results
We measured the horizontal angles and spatial distances between pillars and the IGS station. Since theantenna reference point (ARP) of the IGS station is notdirectly observable, we averaged the horizontal angles
to the left and the right side end of the choke ring antenna, and used their mean value in the following calculation. Regarding the distance from the pillars to the
IGS station, we first measured a spatial distance from

We first calculated coordinates of pillars, the VLBI
ground marker, ARP of IGS, and the targets inside thecabin in the local frame with least squares adjustment.
Then we fit circles or arcs to the coordinates of the targets to estimate the azimuth and elevation axes. The
azimuth axis was estimated as a straight line connecting the center of four circles which correspond to the82

Munekane et al.

Fig. 2: Observations inside the antenna cabin for estimating theazimuth and elevation axes. The TS was put on the cabin base,which does not follow the antenna movement.

Fig. 4: Red, blue, and light blue dots show the estimated po-sitions of targets with the telescope rotated around the azimuth
axis, elevation axis at azimuth of 125 degree, and elevation axis
at azimuth of 215 degree, respectively. Red, blue, and light bluelines represent the corresponding axes.
Fig. 3: Observations of the targets on the cabin wall. We ob-served the targets from the TS while rotating the antenna azimuth(left) and elevation (right).

trajectories of four targets. Likewise, the elevation axis
was estimated as a straight line connecting the centerof two arcs which correspond to the trajectories of twotargets. The elevation axes were estimated for azimuthof 125 degree and 215 degree. The estimated azimuth
axis and two elevation axes are shown in Fig. 4.
We calculated offsets and angles between the azimuth axis and two elevation axes (Fig. 5). Offsets
between the azimuth axis and elevation axes for azimuth of 125 degree and 215 degree were 0.2 mm and
0.1 mm, respectively. The angles between the azimuth
axis and two elevation axes were 90.0006 degree and89.9954 degree, respectively.
Finally, we calculated the local tie vector between
the IVP of VLBI antenna and the IGS reference pointin the geocentric frame (Table 1). To confirm our calculation, we independently calculated the local tie vector with the adjustment software pyaxis (LINZ, 2015).
We found that the differences of the local tie vectors between those by our calculations and those by
pyaxis were negligibly small in practical use though
they slightly exceed the standard deviations of 0.6 mm,

Fig. 5: Offsets and the orthogonality of the axes. Line colors are

the same as shown in Fig. 4.

0.6 mm, and 0.5 mm for x, y, and z component, respectively.

Collocation Survey at Ishioka
Table 1: The estimated local tie vector between the IVP of the83of the local tie vector, we will conduct the same survey

VLBI antenna and the IGS reference point in the geocentric refin a different season in 2019.
erence frame.
X (m)
Y (m)
Z (m) Baseline (m)Acknowledgements We would like to thank Land InformaIVP → ISHI
−12.7427 10.8578 −37.0948 40.6976
tion New Zealand (LINZ) for making the pyaxis software pubIVP → ISHI (pyaxis) −12.7408 10.8612 −37.0957 40.6987∆−0.0019 −0.0034 0.0009−0.0011 licly available (https://github.com/linz/python-linz-pyaxis). We
acknowledge Dr. Chris Crook at LINZ for his assistance for theuse of the software.

4 Summary
We carried out the collocation survey at the Ishioka
geodetic station in November 2018. The IVP of the
VLBI antenna was determined as the intersection of azimuth and elevation axes, which were estimated by the
TS observations of the targets inside the cabin from thecabin base. We found that the Offsets between the azimuth axis and elevation axes are sufficiently small, andthe orthogonality of the axes hold to a high precision.
Then, we successfully estimated the local tie vector between VLBI and GNSS reference points with sufficientaccuracy. In order to investigate the seasonal variation

References
Ishimoto M, Umei M, Wakasugi T, et al. (2016) Status on the
Ishioka Geodetic Observing Station. IVS NICT-TDC News,36, 9–12
Land Information New Zealand 2015 - Warkworth Observatory
Local Tie Survey Land Information New Zealand Record,
A1387321
Matsuzaka S, Hatanaka Y, Nemoto K, et al. (2002) VLBI-GPS
Collocation Method at Geographical Survey Institute. In:
N. R. Vandenberg, K. D. Baver (eds.): IVS 2002 General
Meeting Proceedings, NASA/CP-2002-210002, 96–100

Progress and Current Status of the VGOS Project at theMetsähovi Geodetic Research Station
N. Zubko, J. Näränen, N. Kareinen, J. Eskelinen, M. Poutanen

Abstract A new VGOS radio telescope has been installed during the summer 2018 at Metsähovi Geodetic
Research Station, Finland. The manufacturer has commissioned the telescope in 2018–2019. Work on theantenna control software and communication with the
VLBI Field System is underway. Integration of the signal chain components is moving forward. A broadband
receiver with a quad-ridge feed horn (QRFH) operating at frequency range of 2.4 − 14.1 GHz and filteringand pre-amplifier modules have been manufactured by
IGN-Yebes technology development center. They are
expected to be delivered to Metsähovi during the fallof 2019. The DBBC3 and Flexbuff recording system
has been installed and partly tested. Integration of thesignal chain components has been planned for 2019–2020. Test observations of the complete VGOS telescope system are expected by the end of 2020.

core sites of the Global Geodetic Observing System(GGOS). It is located in Southern Finland (60.2o N,
24.4o E).
Metsähovi is one of the few geodetic stations
that has all major geodetic observing instruments colocated. These include satellite laser ranging (SLR),
very long baseline interferometry (VLBI), global
navigation satellite systems (GNSS), superconducting
and absolute gravimeters, and a DORIS beacon. The

Keywords VGOS · Telescope · Hardware

1 Introduction
The new radio telescope dedicated for the VLBI
Global Observing System (VGOS) has been installedat the Metsähovi Geodetic Research Station (Fig. 1).
Metsähovi station is a key infrastructure of the Finnish
Geospatial Research Institute (FGI) and one of the
Natalyia Zubko · Juri Näränen · Niko Kareinen · J. Eskelinen ·Markku Poutanen
Finnish Geospatial Research Institute (FGI), National Land Survey of Finland, Geodeetinrinne 2, FI-02430, Masala, Finland(Correspondence: nataliya.zubko@nls.fi)

Fig. 1: The VGOS telescope at Metsähovi Geodetic Research
Station.

84

VGOS Metsähovi

Ministry of Agriculture and Forestry has allocateda special funding for the renewal of Metsähovi
instruments and infrastructure during 2012–2018.
The VGOS project in Finland has been started in
the beginning of 2016. It is funded by the National
Land Survey of Finland together with the Finnish Ministry of Forestry and Agriculture.

2 Telescope
The 13.2 m parabolic dish antenna has been designed
by MT Mechatronics GmbH. The main technical characteristics of the telescope are described in the Table 1.
The telescope arrived to the site in the middle ofJune 2018 and the work on telescope assembling continued until end of the August 2018. Fig. 2 showssome phases of assembling the telescope. The manufacturer has commissioned and evaluated telescope
performances during 2018–2019. A site acceptance has
been performed in June 2019. We plan to start our own
telescope tests together with receiver after its arrivaland installation in autumn 2019.
The design of the telescope also includes a steel
pedestal, making it different from other telescopes produced by the same manufacturer (e.g. telescopes installed at Onsala or Yebes observatories). Special measures were taken to provide temperature stability andits monitoring in the pedestal to ensure the reference
point stability. A system for constant temperature andhumidity control along the pedestal has been installed.
The pedestal’s temperature is monitored with 12 temperature sensors. In the future we plan to use sensor’s
data for the characterisation of the system.

Table 1: Telescope technical characteristics

Title
Description
Antenna mountStandard azimuth-elevation type
Reflector optics
Cassegrain, ring focus
Diameter of the main reflector 13.2 m
Surf. accuracy of the main refl. < 0.3 mm rms
Surf. accuracy of the subrefl. < 0.1 mm rms
Antenna motion
Velocity in Az axis
12 deg/s
Velocity in El axis
6 deg/s
Acceleration in Az axis
2.5 deg/s2
Acceleration in El axis
2.5 deg/s2

85

Cable wrap is placed on the ground level of thepedestal. The Antenna Control Unit together with thepower cabinet are located on the first level (Fig. 3).

3 Signal chain
The telescope will be equipped with a broadband
receiver manufactured by IGN-Yebes technology
development center. Estimated site installation timeis October 2019. The receiver has quad-ridge feedhorn (QRFH), designed to measure both linear polarisations at frequency range of 2.1 − 14.1 GHz.
The signal from the receiver will pass trough thefiltering and pre-amplifier modules, each polarisation
component is divided to low (2.1 − 5.6 GHz) and high(3.6 − 14.1 GHz) frequency bands. Then the signal istransferred over fiber link to the backend located in
the instrumentation room of the station main building.
Before signal digitization it will pass through the filterbank module, where the signal will be divided to 5channels (both vertical and horizontal polarisation
components) according to the Table 2.

Table 2: The selected frequencies for the filtering module

IF1
IF2
IF3
IF4
IF5
GHz
GHz
GHz
GHz
GHz
2.1 − 4.0 3.6 − 7.6 4.6 − 8.6 7.6 − 11.6 10.6 − 14.1

The digital backend is DBBC3, produced by HatLab Tuccari et al. (2017). It has been installed in instrumentation room and its testing is planned after thereceiver installation. A Flexbuff system will be used forsignal recording.
An upgrade to internet fiber connection is planned,
so data can be e-transferred with high speed to the correlator.

4 Future plans
The integration and testing of the complete signal chain
together with telescope is planned for the 2020. After
successful test of our complete system we expect tojoin VGOS network observations in test mode.

86

Zubko et al.

Fig. 2: Telescope construction.

Fig. 3: First level of the pedestal with ACU and other equipment.

References
Tuccari G, Alef W, Wunderlich M, et al. (2017) DBBC3: The
new Flexible, Wide-band VLBI Backend. In: R. Haas, G. El-

gered (eds.): Proc. 23rd EVGA Working Meeting, 78–80

Centralized Monitoring of VLBI Antennas for Seamless
Auxiliary Data
A. Neidhardt, E. Barbieri, J. Bachem, M. Schönberger, M. S. Hameed, L. Carlin, R. Aktas, S. Jingyao,
A. Szomoru

Abstract Twelve institutes from eight different countries have teamed up in the JUMPING JIVE project,currently financed by the Horizon 2020 Framework
Program of the EU for four years. The project is led
by JIVE, the Joint Institute for VLBI ERIC, located in
Dwingeloo (the Netherlands). The Technical University of Munich with the Geodetic Observatory Wettzell
participates in this project integrating monitoring systems for global VLBI interfaces. Existing techniques
were analyzed and compared. A test setup was implemented selecting the best-rated solution. It was installed at the Wettzell observatory. The current status of
the monitoring task with a focus on gathering seamlessauxiliary data is described here, which is also a benefit
for the IVS Task Force of Seamless Auxiliary Data.

1 Introduction
In 2014, the IVS task force for seamless auxiliary
data was founded during the IVS General Meeting inShanghai. Goal of this group is to define data which
are currently available only in session log files but
would be permanently required for analysis. But before the selection of data could be done, a framework
had to be created to communicate, store and archive
such data on a centralized monitoring system. As task
8 of project ”Jumping JIVE” (see JIVE, 2019) about
centralized real-time monitoring of the EVN supportedby the Technical University of Munich ideally fed also
for seamless auxiliary data, the infrastructure was extended. A well tested version is now available and under test with the O’Higgins antenna (Antarctica), theantennas of the Wettzell observatory (Germany), andpartly with AGGO in La Plata (Argentinia).

Keywords Monitoring · Seamless auxiliary data

2 Technical implementation of themonitoring system
Alexander Neidhardt
FESG Wettzell, TU of Munich, Geodetic Observatory Wettzell,
Sackenrieder Str. 25, DE-93444 Bad Kötzting, Germany
E. Barbieri · M. S. Hameed · L. Carlin · R. Aktas · S. Jingyao
FESG, TU of Munich, Arcisstr. 21, DE-80333 Munich, Germany
J. Bachem · M. Schönberger
BKG, Geodetic Observatory Wettzell, Sackenrieder Str. 25, DE93444 Bad Kötzting, Germany
Arpad Szomoru
Joint Institute for VLBI ERIC, Oude Hoogeveensedijk 4, NL7991 PD Dwingeloo, The Netherlands(Correspondence: neidhardt@fs.wettzell.de)

The monitoring system consists of two data streams:
one uses dynamical web pages from a web server on
the NASA Field System PC (see other paper), the otheris based on mechanisms of the professional monitoring
system ZABBIX. Sites can individually decide which
streams they want to support.
If the general data set from the NASA Field System
is supported (offering 110 parameters from the NASA
Field System shared memory in real-time), the station staff must install and configure the e-RemoteCtrl
server using predefined HTML templates dynamicallyfilled by the server. No additional program, like a web
87

88

server, is required. It only supports the passive monitoring without any commanding interface. The configuration (e.g., port or update rates) can be made individually at each site. All template files can be adapted
by station staff to prepare them for individual requirements, as long as the standardized tags are used which
identify the value items. The dynamical updating of the
web pages is then done by the server. It is suggested
that all antennas at least support this stream.
If additional system parameters should be monitored, the use of ZABBIX agents and a proxy serveris suggested. Zabbix is a monitoring platform supporting the collecting and presentation of monitoring data
(Zabbix, 2018). A ZABBIX agent runs on different
platforms and collects data such as CPU, memory, disk
and network access (Zabbix, 2019). Agents can evenrun on platforms with limited resources. Agents can be
active, getting a list of value items to be monitored andsending the values actively to a central server. They canalso be configured to be passively waiting for value requests and replying with current data.
ZABBIX agents already include a set of items, likenetwork status with number of transmitted bytes or errors, CPU load, memory use, disk volumes, process
status, file information, text logs, or operating system
details.
A ZABBIX proxy acts like a central monitoring
server collecting data from different ZABBIX agents.
Data are buffered locally to be requested by a ZABBIX
server at the monitoring center. ZABBIX proxies are
the key technology to distribute data from an antennasite to a central monitoring archive.
Additionally, proxies can use SNMP calls to request data from specific devices, like UPS, rack coolers, and so on. Therefore, ZABBIX offers a huge set of
possibilities already include.

Neidhardt et al.

Additionally, a Linux script ”autossh run.sh” is offered, which establishes a secure SSH connection between the site-specific PC (e.g. the NASA Field System PC or a separate monitoring PC) and the ZABBIX
server at Wettzell using the SSH key (see Fig. 3). The
script also keeps the connection alive or reestablishes
it after a blackout or failure situation. The SSH communication is used for the creation of reverse tunnels
from the ZABBIX server to a site-specific PC which
are used for the transfer of monitoring data. Each siteis allocated with an individual HTTP port and an individual ZABBIX port as end-point of the tunnel on the
ZABBIX server.
On the central monitoring server itself, scripts fetch
a copy of the web pages from the NASA Field System
PC via the HTTP-tunnel (usually each second) and extract all related values from the pages using the predefined, standardized tags. If individual, site-specific tags
are used, specific scripts can be used. The programs
send the extracted values dynamically to the ZABBIX server and into the database. The ZABBIX server
also uses the site-specific proxy via the ZABBIX port
to request additional monitoring data. To simplify themonitoring of additional data, station staff must create

3 Connection to a seamless auxiliary
data archive
Currently, the first productive system for a seamlessauxiliary data archive is installed at the Wettzell observatory. Due to security restrictions of the different sites,
only direct one-to-one Secure Shell (SSH) connections
between a site-specific PC and the central monitoring
server e.g. at Wettzell observatory are allowed. Stations
get an SSH key file and an individual user account.

Fig. 1: Connecting site monitoring to a centralized monitoringarchive.

Seamless Auxiliary Data89

own templates for ZABBIX hosts (monitoring control
points), so that hosts and corresponding presentations
can directly be uploaded to the central ZABBIX server.
The timing of these requests is defined via the ZABBIX
server web page.
An additional script ”ZabbixAPI.py” on the servermachine reads required seamless auxiliary data fromthe ZABBIX database and copies them into daily files(one per item). These files are organized with directories based on year, month, antenna name, and sensor name. Current tests extract temperature, humidity,
and pressure. The internal structure of each file is very
simple. It contains the ZABBIX item identifier whichshould never change, UTC clock in Unix time, UTC
clock in regular UTC, and the value for that time stamp(see Fig. 2).

Fig. 3: ZABBIX web interface to seamless auxiliary dataarchive.
Fig. 2: Extracted seamless, auxiliary data of one sensor.

5 Joining and supporting the seamlessauxiliary data archive

4 Using the seamless auxiliary dataarchive
To use data from the archive, a user account and a web
page account is necessary. It can be requested from theadministrator of the archive. The web page account canbe used to access the ZABBIX web pages (see Fig. 3).
They offer plots, charts and screens with historic data
for the last three month. The idea is to offer a fast way
for plotting and diagnosing specific system situations
and behavior.
The user account can be used to download files
archived on the file system. The idea behind is to offer a simple way to get a whole collection of data for alonger time period for analysis.

A first technical solution for continuous data acquisition is now available with the system described. Therefore, both antennas and analysts should now start tojoin and support the archive.
On the one hand, stations should install at least thee-RemoteCtrl software and the SSH-communication tosend in data in real-time. If additional sites will participate, developers and administrators can test the system and communication under different circumstances
over world area networks. On the other hand, analysis
centers should discuss requirements to define specifications especially about:

90

Neidhardt et al.

• which parameters are required for analysis• which time intervals are required• which format is required in best case
• which stations can and will participate• which station log books with meta-data are useful• ...

tions lead to different issues. The idea is now to motivate antenna sites and analysts to participate.
Acknowledgements This project has received funding from theEuropean Union’s Horizon 2020 research and innovation programme under grant agreement No 730884 - JUMPING JIVE.

Any support is welcome!

References
6 Conclusion and outlook
The system is under test with the Wettzell antennas
on a final productive server. There is a continuous improvement because different computer network situa-

JIVE (2019) JUMPING JIVE https://jive.eu/jumping-jive,
Download 2019-07-15
Zabbix LLC (2018) The Ultimate Enterprise - class Monitoring
Platform https://www.zabbix.com/, Download 2018-09-13
Zabbix LLC (2019) Zabbix Agent https://www.zabbix.com/
zabbix agent, Download 2019-07-15

Remote Access to the NASA Field System via Web Browser
A. Neidhardt

Abstract Remote control offers advantages for operation of VLBI radio telescopes. Night shifts and weekend shifts can be operated remotely. Engineers win theability to support student operators or fix failure situations from home. Operation centers can monitor important health states. Using the remote control software”e-RemoteCtrl” for the NASA Field System, remotecontrol and attendance have been possible for years.
During the past years, ”e-RemoteCtrl” was extended
with a rudimentary, integrated web server. Therefore,
operators are now able to access the Field System parameters via web browser. 110 parameters are accessible and can be extended with individual station-specificvalues.

Keywords Remote access · Operation · Web server

1 Introduction
A new browser-based access to the NASA Field
System was shown at the IVS General Meeting inLongyearbyen, Spitsbergen, Norway. Since then, thesoftware has been continuously updated and bugs
were fixed. Currently, tests are ongoing to use it
for O’Higgins, Antarctica and AGGO in La Plata,
Argentinia.

Alexander Neidhardt
FESG Wettzell, TU of Munich, Geodetic Observatory Wettzell,
Sackenrieder Str. 25, DE-93444 Bad Kötzting, Germany(Correspondence: neidhardt@fs.wettzell.de)

2 Current version of web front-end
The browser-based monitoring uses the e-RemoteCtrl
environment developed during the NEXPReS project
funded by the European Union (see Ettl et al., 2012;
Neidhardt, 2017). The original remote access is
extended with an elementary web server thread whichis part of e-RemoteCtrl. It just supports the needsof remote monitoring of Field System data. It reads
template files and dynamically replaces specific tagswith corresponding data. The server behavior can beadapted by changing the configuration file.
The web pages can be used with a standard webbrowser (tested are Chrome, Firefox, and Internet Explorer) all over the local network when connecting
to the HTTP port of the e-RemoteCtrl server on theNASA Field System PC. All pages are automatically
updated according to a predefined timing.
The following web pages are currently supported:• System Status Monitor• Mark5 Remaining Capacity• System Temperatures• Log• Webcam (requires correct settings in the configuration file)• Antenna (requires adaption of the e-RemoteCtrlspecific station code)• Station Monitoring (requires regular updates ofstation-specific HTML file)• Phase Cal Monitoring (for Mark4 systems)
Standard settings offer a web monitoring port 8080.
A controlling port 8081 is under development. One canget the latest release of the software from Wettzell observatory. It also supports the IVS task force for seamless auxiliary data (see separate paper). Secured Inter91

92

Neidhardt

Fig. 1: Web-based extension of e-RemoteCtrl software and corresponding web front-end.

net access via HTTPS from all over the world is additionally supported using a centralized monitoring infrastructure currently located at Wettzell observatory(see separate paper).
Fig. 1 shows an overview of the new web-based access.

3 New elements of the front-end
Keeping the general structure and also the pure, elementary HTML with only some Javascript sections,some extensions were made. The Mark5 Remaining
Capacity frame now shows a volume bar graphicallypresents the fill state of the modules. It changes fromgreen to red if a fill state of more then 97 percent isreached and directly works as a notification. The Phase
Cal Monitoring frame is not anymore part of the shownelements in the standard installation because it is justavailable for older Mark4 systems or systems supporting that feature in the NASA Field System.

Additionally, a demonstration of the Station Monitoring frame was created at the 20m antenna of the
Wettzell observatory. A shell script fetches stationspecific monitoring data, like dewar information,
frequency offsets between maser or local time andfrequency distributors and some master clocks, andcounter values for GPS minus fmout and Mark5 frequency delays. The shell script is activated as a cronjob
each minute, reads all data and echos corresponding
HTML structures to the Station Monitoring web page.
The shell script also interprets values against trigger
levels and colorizes such values with color codes ifthey are out of defined limits. Each antenna must create
and update its own Station Monitoring page. It canalso be used for antenna monitoring data if the station
code of e-RemoteCtrl should not be programmed.
For further processing on centralized system monitoring servers, individual values in the station-specificsection should be tagged with characterizing identifiersin the same style as the official values.
Very useful is the already existing classification ofNASA Field System errors with different color codes toRemote Accessseparate between warnings and real errors in the Log
section. Warnings in this case classify situations with
reduced data quality. Errors are issues with no or broken data recordings. The severity level can be definedin the configuration file of e-RemoteCtrl.

93

the individual NASA Field System PC. Current student
project at the Technical University of Munich implement a more sophisticated version of the web pages
especially for mobile devices.

References
4 Conclusion and outlook
The current web interface is permanently used by operators of the VLBI telescopes of the Wettzell observatory. Web pages are also accessible from the Internet as copies on a centralized monitoring server offering a regular web browser without direct access toEttl M, Neidhardt A, Schönberger M, et al. (2012) e-RemoteCtrl:
Concepts for VLBI Station Control as Part of NEXPReS; In:
D. Behrend, K. D. Baver (eds.): IVS 2012 General Meeting
Proceedings, NASA/CP-2012-217504, 128–132
Neidhardt A (2017) Applied Computer Science for GGOS Observatories. Communication, Coordination and Automationof Future Geodetic Infrastructures. Springer International
Publishing Switzerland, ISBN 978-3-319-40137-9.

Space Low-Frequency Radio Observatory and the Earth-Moon
VLBI Experiment
W. Zheng, T. An, J. Zhang, L. Liu

Abstract A Space Low-Frequency Radio Observatory
project is proposed. It aims at high resolution observations of the compact radio sources, e.g. black hole,pulsar, exoplanets, etc. The project plans to send two
30 meter-diameter radio telescopes to the earth elliptical orbit. The space telescopes could work together
with the earth-based VLBI (Very Long Baseline Interferometry) network, Square Kilometre Array (SKA)and Five-hundred-meter Aperture Spherical radio Telescope (FAST) to achieve high resolution and sensitivity. This paper describes the general mission concept,
the technique parameters and the operational modes.
The major scientific objectives cover broad astronomical fields. It offers astronomers unique opportunities tomake revolutionary discoveries in the field of exoplanets, pulsars, gravitational wave electromagnetic counterparts, as well as probing the evolutionary historyof the Universe. The unprecedented high resolution
enables the accurate astrometry, allowing for supplying precise localization of pulsars, FRBs (Fast Radio
Bursts), GRBs (Gamma Ray Bursts) at milliarcsecond(mas) level. In the subsequent China’s Lunar Exploration Project, there will be a chance of the Earth-moon
VLBI experiment. It is possible to place the space telescope in the lunar orbit or on the moon surface in the
future.

Keywords Space low-frequency radio observatory ·Space VLBI · Earth-Moon VLBI experiment

Weimin Zheng · Tao An · Juan Zhang · Lei Liu
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China(Correspondence: zhwm@shao.ac.cn)

1 Introduction
The limitation of the ground VLBI angular resolution
is restricted by the Earth diameter. Given the same
frequency, to get the higher angular resolution, SpaceVLBI (SVLBI) is unique choice. SVLBI is a technique in which an array of space radio telescopes oran array of ground radio telescopes observes a sourcein conjunction with one or more orbiting radio telescopes (Ulvestad, 1999). It can employ Space-Earthbaselines or Space-Space ones to get the better uv coverage and higher angular resolution. After the first generation SVLBI projects of VLBI Space Observatory
Program (VSOP) and RadioAstron, there are considerations of the next generation SVLBI with more spacetelescopes, more big space antennas to get the better uv
coverage and sensitivity. The observation frequency ismore focused on millimeter band and cm-dm band oreven lower (Gurvits, 2019).
The earth-based Chinese VLBI Network (CVN)
plan to extend to the space in the future and there
are several proposals. One proposal is the Space
Low-Frequency Radio Observatory, which is proposed
to image the fine structure of compact celestial objects
such as black hole, pulsar and so on. It offers astronomers unique opportunities to make revolutionary
discoveries in exoplanets, pulsars, gravitational wave
electromagnetic counterparts, and to probe the evolutionary history of the Universe. The unprecedented
high resolution enables the accurate astrometry,allowing for supplying precise localization of pulsars,
FRBs, GRBs at mas level. The mission plans tolaunch two 30 meter-diameter radio telescopes into
an earth elliptical orbit, and works together with theearth-based VLBI network, Square Kilometre Array(SKA) and Five-hundred-meter Aperture Spherical94

Low-Frequency Radio Observatory

radio Telescope (FAST) to get very high resolution
and very high sensitivity. The low frequency observatory will carry out observation in radio band from30 MHz to 1.7 GHz. In the subsequent China’s Lunar
Exploration Project (CLEP), there will be a chance of
the Earth-moon VLBI experiment, using the antennaof the lunar orbit Tracking and Data Relay Satellite(TDRS) to construct the first Earth moon space VLBI
experimental system. Because the Earth-moon VLBI
baseline is over 300 km, the experiments of astrometry, astrophysics and the deep-space tracking will be
carried out. After this, a 10 m level radio telescope isplanned to be constructed on the moon surface in the
future by the astronaut.

2 Space Low-Frequency Radio
Observatory
Over the past half a century, SVLBI has unique applications in high-resolution imaging of fine structureof astronomical objects and high-precision astrometry,owing to the key long space-Earth or space-space baselines beyond the Earth’s diameter. China has been actively involved in the development of space VLBI in
recent years.
Supported by the Strategic Priority Program on
Space Science, CAS, the researches of the space mmwavelength VLBI array (SMVA) has been carried out
since 2012. SMVA, the long mm-wavelength space
VLBI including two 10 m space telescopes working at
frequencies up to 43 GHz. These two telescopes willobtain observations together with ground telescopes toachieve a highest resolution of 20 micro-arcseconds(µas). The main motivation is to obtain a better understanding of AGN (Active Galactic Nuclei) jet physics
and the emission structure around the supermassive
black holes (SMBHs) (Hong et al., 2019). Despite important progress, some technical challenges in the areaof space millimeter waves remain difficult to overcomein the short term.
Because many unique scientific studies can be donein the low frequency, including studies of the early Universe and cosmological structure formation, directly
resolving the SMBH binaries, precise positioning anddistance measurements of pulsars and other transients,
etc. The suitable space environment is beneficial to
low-frequency space radio research and technologies,

95

Fig. 1: Space Low-Frequency Radio Observatory with two
30 meter parabolic antennas.

low frequencies are easier to achieve than high frequencies.
With the completion of Five hundred meter Aperture Spherical Telescope (FAST) and the imminent
start of the Square Kilometre Array phase1 (SKA1),
we have entered a new era. The establishment of a generalized space low-frequency space radio observatory
can achieve high sensitivity and high resolution in both
low-frequency bands with the help of large groundbased low-frequency telescopes such as FAST, SKA,
GBT (Green Bank Telescope) and space VLBI technology.
The Space Low-Frequency Radio Observatory(SLRO) involves launching dual space telescopes withdiameters of 30 m into large elliptical orbits withheights between 2,000 km and 90,000 km, working
with FAST, SKA, GBT, it will allow imaging of
the ultra-low frequency radio sky at unprecedented
high resolutions (0.4 mas at 1.67 GHz and 20 mas at
30 MHz) and with high sensitivity at the sub-mJy level(An et al., 2019).

2.1 Major scientific goals
Compared with previous space VLBI program, thebaseline sensitivity of the present Space VLBI mission
increases by a factor of 10 or higher owing to adding
the newly constructed giant ground telescopes, (e.g.,
FAST, SKA1), and the resolution is 10 times higher
than ground-only VLBI network below L band. The
combination of two space telescopes significantly im-

96

Zheng et al.

Fig. 2: Major scientific goals and their corresponding observation frequencies.

proves the uv coverage on space-ground baselines, andthus increases the image performance. We expect todetect weak and compact population of Galactic (e.g.,radio stars, pulsars) and extragalactic radio sources(e.g., radio quiet AGN) which are not well known
yet. The space VLBI at the 30-300MHz frequency
range will open a new window to observe the radio
emission from Jovian-type exoplanets, marking animportant step in exoplanet studies, and also offers an
opportunity to observe the total power spectrum of
EoR and Cosmic Dawn. The Major scientific goals
and their corresponding observation frequencies arelisted in Fig. 2.

!Fig. 3: Earth-moon VLBI experiment.

2.3 Operational modes
2.2 Mission concept

The space low frequency radio observatory consistsof two space radio telescopes each equipped with a
30 meter antennas. The main parameters of the mission are listed in Tab. 1. The observatory will carryout space-ground, space-space VLBI and single dishspace based observations. Besides the space radio telescope, a Space VLBI scientific data center will be built
in the Sheshan campus of Shanghai Astronomical Observatory. The planned construction period is 7 years
and is divided into 2 stages. In the first stage (5 year),the first satellite will be delivered in orbit to carry out
single dish and space-ground VLBI observations. Also
the ground facility will also finish construction in thisstage. In the second stage (2 year), the second satellite
will be in operation.

Three operational modes are summarized as follows:• Space-ground VLBI. Unprecedented super VLBI
network: two space-based VLBI Stations plus
large ground telescopes (SKA1, FAST, QTT, etc.).
New window (30 − 300 MHz) for space VLBI.
• Space-space VLBI (single baseline). Spacebased VLBI, long integration time, fast responseof super-burst of OH masers, auroral radiationfrom extrasolar systems.
• Space-based single dish. EoR power spectrum,
pulsar timing array, etc.

2.4 Key technologies
The construction and operation of large space radio telescopes are of huge challenge for ChineseLow-Frequency Radio Observatory

97

Table 1: Main parameters of the mission.

Parameter
Setting
Antenna size
30 meter
Orbit height
2,000 km - 90,000 km
Inclination angle
28.5◦
Frequency configuration 30 MHz, 74 MHz, 330 MHz, 1.7 GHz
Weight
1.5 ton per satellite
Resolution
20 mas (30 MHz), 8 mas (74 MHz), 2 mas (300 MHz), 0.4 mas (1.7 GHz)
Sensitivity
sub-mJy (baseline, 10 min integration), 1 mJy/beam (image, 1 hour, 1.6 GHz)
Ground Station
FAST + SKA + other large VLBI antennas

Relay Satellite (TDRS) and CVN ground antennas toconstruct the first Earth moon space VLBI experimental system. We hope using the earth-moon VLBI system to verify the key space VLBI technology. Because
the Earth-moon VLBI baseline is over 300 km, theexperiments of astrometry, astrophysics and the deepspace tracking will be carried out. After this, a radio
telescope is planned to be constructed on the moon surface in the future by the astronaut. The main parametersof the experimental SVLBI are:Fig. 4: Fringes of rk01yv, RA-Spekr-R antenna on board; WB-

WSTRBORK, AR-ARECIBO. C-band VLBI observation.

astronomers and engineers. As a result, experts in different fields must work together to overcome various
kinds of difficulties. In particular, we summarize thekey technologies involved in current low frequency
radio observatory.
• Large diameter space antenna production and inorbit calibration.
• Large inertia space telescope fast maneuver andstabilization.
• Low frequency space telescope electromagnetic
shielding.
• Low frequency VLBI coordinated observation.

3 Earth-moon VLBI experiment
In the subsequent China’s Lunar Exploration Project,
there will be an Earth-moon VLBI experiment, using
the relay antenna of the lunar orbit Tracking and Data

• Antenna diameter: 4.2 m• Band: X• Orbit: 200 km × 8,500 km• Length of baseline: 400,000 km
With the support of Astro Space Center (ASC) of Lebedev Physical Institute of Russian Academy of Sciences(RAS), we have obtained the space VLBI fringe of RadioAstron observation data using CVN correlator. To
process the RadioAstron space-ground baseline data,
CVN correlator updates the delay model and the data
format of RDF (RadioAstron Data Format).
We have processed the data observed on 2014
(code: rk01yv) and obtained fringes (Fig. 4).

4 Conclusions
In the era of FAST and SKA, the low frequency radio
astronomy will be the new frontier. Space VLBI is the
future direction of CVN. A proposal of a Space LowFrequency Radio Observatory with two 30 m space antennas has been put forward.
Space VLBI is the future direction of CVN. The
low-frequency radio observatory will achieve both highsensitivity and high resolution, and are expected tomake innovative achievements in early cosmology, supermassive black holes, and more. To advance this98

project, we hope to conduct technical verification in thesubsequent lunar VLBI project.
Acknowledgements This work is sponsored by the Natural Science Foundation of China (11573057), the Key Laboratory ofRadio Astronomy of CAS, Shanghai Key Laboratory of Space
Navigation and Positioning Technology, Shanghai the CAS Key
Technology Talent Program, the Program of Shanghai Subject
Chief Scientist, Advanced Research Project of Strategic Priority Program on Space Science, CAS (XDA15016100), CAS Key
Technology Talent Program and Ten-thousand Talents Program,Shanghai Leading Talents program, and Fundamental Science
Data Sharing Platform (DKA2017-12-02-09).
We would like to express our gratitude to the researchers(Alexey Rudnitskiy, Andrey Andrianov, Sergey Likhachev andso on) from Astro Space Center (ASC) of Lebedev Physical Institute of Russian Academy of Sciences (RAS) who not only pro-

Zheng et al.

vided the raw data and helped us to understand RadioAstron system and the observation mode.

References
Hong X, Shen Z, An T, et al. (2019) The Chinese Space
Millimeter-Wavelength VLBI Array – a Step toward Imaging the Most Compact Astronomical Objects. Acta Astronaut., 102, 217–225, doi:10.1016/j.actaastro.2014.05.026
Gurvits L I (2019) Space VLBI: from first ideas to operational
missions. ASR, doi:10.1016/j.asr.2019.05.042
An T, Hong X, Zheng W, et al. (2019) Space very long baseline
interferometry in China. ASR, doi:10.1016/j.asr.2019.03.030
Ulvestad J S (1999) Space Very Long Baseline Interferometry,
Synthesis Imaging in Radio Astronomy II. In: G. B. Taylor,
C. L. Carilli, R. A. Perley (eds.) ASP Conference Series, 180

An Artificial Radio Signal for VLBI Satellite Tracking
A. Jaradat, F. Jaron, A. Nothnagel

Abstract It has been shown that VLBI observationsof satellites orbiting the Earth bear the potential of improving the frame-ties between terrestrial and celestialreference frames. A dedicated satellite mission, however, is currently not in orbit yet nor is there any satellite emitting a radio signal which is optimal for the observation with VLBI. Here we review the technical feasibility of the generation of a broad-band noise signal,
its amplification, and emission. We find that a satellite could be equipped with the necessary instrumentation with relatively low power consumption. This could
make it an interesting option, e.g., for GNSS satellites,
thus enabling co-location in space.

Keywords VLBI transmitter · Satellite · GNSS

1 Introduction
Observing Earth satellites with ground based VLBI isof increasing interest for geodetic applications. The
reason for this is that it has been shown that including
satellite observations into geodetic VLBI sessions canimprove the frame ties between celestial and terrestialreference frames, see Fig. 1 (Anderson, 2015) and
Fig. 2 (Plank, 2013).

Ahmad Jaradat · Frédéric Jaron1 · Axel Nothnagel
Institute of Geodesy and Geoinformation, University of Bonn,
Nußallee 17, DE-53115 Bonn, Germany(1) now at Max Planck Institute for Radio Astronomy, Auf dem
Hügel 69, DE-53121 Bonn, Germany(Correspondence:
bonn.de)s7ahjara@uni-bonn.de,

nothnagel@uni-

Fig. 1: VLBI observations of Earth satellites fill the missing

direct link between the celestial reference frame and the dynamic reference frames of satellites. Figure taken from Anderson(2015).

Several experiments have been made to observe
GNSS satellites with VLBI radio telescopes by Haas
et al. (2014); Tornatore et al. (2014); McCallum et al.
(2016), but neither the frequency setup nor the signal power was adequate to the usual VLBI observing
mode and caused a number of problems. Furthermore,
Hellerschmied et al. (2016) observed Cubesat which
was too fast so that the tracking caused problems and it
only had DOR tone emission which is problematic for
VLBI post-processing and analysis.
In the time of writing there is not any satellite mission in orbit which has been designed for the purposeof being observed with VLBI.

2 Link budget
In order to be suitable to be observed by geodetic
VLBI, the transmitted signal should be similar to theradiation of a quasar in terms of spectrum and intensity.
99

100

Jaradat et al.

we assume to be k = 0.5 here. The antenna gain of
Eq. (2) is plotted in Fig. 4 for different wavelengths(λ = 15, 3.8, 2.1 cm, i.e., frequencies ν = 2, 8, 14 GHz).
Path losses: While the signal travels from thesatellite to the antenna, it suffers from intensity attenuation due to free path loss (FPL) and atmosphericattenuation.

Fig. 2: Principle of a space tie. A satellite is tracked simulta-

neously by different space-geodetic techniques, realizing a platform for co-location in space. Figure taken from Plank (2013).

In other words, the spectrum has to be as flat as possible and it should cover a frequency range from 2 to
14 GHz to be suitable for both legacy S/X observations
and the upcoming VGOS. Furthermore, a trade off has
to be done for the received intensity. On the one hand,
the received intensity has be similar to a typical quasar,in order to avoid any change in the attenuation level at
the telescopes. On the other hand, since the satellite ismoving, the integration time has to as short as possible,
thus, the received intensity has to be relative large. The
initial assumption could be ∼ 1 − 10 Jy.
In order to compute the intensity of the transmitted
signal, the link budget has to be calculated, which is
the total gains and losses of the signal intensity fromthe transmitter to the receiver, which consist mainly of
the the antenna gain and path losses (free path loss andatmospheric attenuation) as shown in Fig. 3:

The FPL can be thought of as the signal spreadingout as an increasing sphere. As the signal has to covera wider area, conservation of energy tells that the energy in any given area will reduce as the area covered
becomes larger. It could be calculated using the following expression (Anderson, 2003):
FPL = 32.44 + 20 log10 (F MHz ) + 20 log10 (Dkm ). (3)Here F is the frequency in MHz and D is the distance between the satellite and the antenna in km. In
the worst case, while the elevation angle  is 5◦ the distance will be 25040.4 km.
Atmospheric attenuations are estimated according to the ITU recommendations (ITU, 2016). With assuming that the total path length between antenna andclouds as source of rain is 5 km in the zenith direction,
which will be 57 km at elevation down to  = 5◦ , andwith standard atmospheric conditions, surface pressure
at sea level of 1013 hPa and humidity of 7.5 g/m3 . Figure 5 shows the attenuation due to the dry and the wet
parts of the atmosphere.

Transmitted signal = Received signal − Antenna gain
+ Path losses.

(1)

Signal consideration: The received signal which
will be studied here has 10 Jy intensity, emitted by a
GNSS satellite (20 000 km altitude), and received by a
13 m antenna (VGOS standard) at 5◦ elevation angle.
Antenna gain: The parabolic antenna gain is givenby (Stutzman and Thiele, 2012)
πd
Antenna Gain = 10 log10 k
λ

!2
,

(2)
Fig. 3: The change of the signal intensity with distance and an-

where λ is the signal wavelength, d is the diameterof the antenna, and k is the efficiency factor, which

tenna gain during propagation a signal from a satellite to a telescope (Link budget).

An Artificial Radio Signal for VLBI Satellite Tracking

101

Fig. 4: Parabolic dish antenna gain at different frequencies and antenna diameter.

Fig. 5: Atmospheric attenuation per kilometer.

3 Instruments
To generate such a signal, a noise generator could be
used, i.e., a noise diode. The intensity of the noise
diode signal is defined by ENR (Excess Noise Ratio),which shows how much the noise source is above thermal noise in its power. Thus, the intensity can be approximated by adding the ENR to a typical thermal
noise level of −204 dBW/Hz. The typical ENR of anoise diode is between 10 and 20. Thus, an amplifier isneeded in order to generate a signal with the required
intensity (see Table 1). Since the bandwidth of the generated signal is wide, i.e., ∼ 12 GHz, a special kind ofantenna should be used in order to avoid any changes in
the gain, phase center, polarization, and radiation pattern across the band. A log-spiral antenna can serve
these requirements (see Fig. 6).

Fig. 6: Log-spiral antenna. Figure taken from Johnson and Jasik(1984).

4 Signal strength
Table 1 shows the link budget results and the minimum
required transmitted intensity considering the properties of the signal as mentioned in Sect. 2.

102
Table 1: Results of the link budget, which shows the total atten-

uation of the signal intensity. Attenuation + received intensity =transmitted intensity.
Frequency
Gain-Loss
2 GHz 8 GHz 14 GHz
Received intensity−260 dBW
dBW Hz−1 m−2◦Free path loss at  = 5
188
200
204
dBW
Atmospheric attenuation
0.5
0.5
1.5
at  = 5◦ , dBW
Antenna gain
−46.5 −58
−63
dBW
Total transmitted intensity−118 −117.5 −117.5
dBW Hz−1 m−2

5 Conclusions and outlook
We have investigated a possible signal to be emitted
from a satellite and observed by geodetic VLBI. The
goal of this is to improve the frame ties between ITRF
and IRCF. We define the main characteristics of thissignal to be close to the radio emission from a quasar
in order to be suitable for the observation with geodetic
VLBI. We computed the intensity of the signal, which
could be emitted from a GNSS satellite by computing
the link budget of the signal.
Furthermore, we looked into the instruments which
could be used to generate and transmit this signal.
Noise diode and amplifier could be used to generate
and amplify the signal. A spiral antenna could be aproper antenna to emit this signal, because it belongs to
the class of frequency independent antennas, which operate over a wide range of frequencies. Further investigations should be done on these instruments in terms ofenvironmental circumstances and power consumption.
The calculations presented here show that an artificial noise signal can be generated at the required intensity. This makes it an interesting option to add to,e.g., a GNSS satellite, thus implementing co-location

Jaradat et al.

in space. Further investigation of the possible emitted
spectrum of the generated signal is needed in order tofind the optimal solution for the entire analysis chain
from correlation to final parameter estimation.
Acknowledgements This research is supported by the Deutsche
Forschungsgemeinschaft, DFG, project number NO 318/14-1.
AJ thanks the Nachlass-Zetsche-Stiftungsfonds for financial support.

References
Anderson H R (2003) Fixed broadband wireless system design.
John Wiley and Sons
Anderson J (2015) Ties between kinematic and dynamic reference frames (D-VLBI). http://www.iap.fr/gagnes/talks/Anderson GAGNES.pdf
Haas R, Neidhardt A, Kodet J, et al. (2014) The Wettzell-Onsala
G130128 experiment – VLBI-observations of a GLONASS
satellite. In: D. Behrend, K. D. Baver, K. L. Armstrong(eds.): IVS 2014 General Meeting Proceedings, Science
Press (Beijing), 451–455
Hellerschmied A, Plank L, McCallum J, et al. (2016) Scheduling of VLBI satellite observations with VieVS. In: A. Nothnagel, F. Jaron (eds.): Proc. First International Workshop on
VLBI Observations of Near-field Targets, 1–5
ITU 2016 Recommendation ITU-R P.676-11 (09/2016)
Johnson R C, Jasik H (1984) Antenna engineering handbook,2nd edition, New York, McGraw-Hill Book Company
McCallum J, Plank L, Hellerschmied A, et al. (2016) Technical challenges in VLBI observations of GNSS sources.
In: A. Nothnagel, F. Jaron (eds.): Proc. First International
Workshop on VLBI Observations of Near-field Targets, 7–10
Plank L (2013) VLBI satellite tracking for the realization offrame ties. PhD thesis, TU Wien
Stutzman W L, Thiele G A (2012) Antenna theory and design.
John Wiley and Sons.
Tornatore V, Haas R, Casey S, et al. (2014) Direct VLBI observations of global navigation satellite system signals. In:
C. Rizos, P. Willis (eds.): ”Earth on the Edge: Science for a
Sustainable Planet”, IAG Symposia, 139, 247–252, Springer,
Berlin, Heidelberg, doi:10.1007/978-3-642-37222-3 32

The Bonn Correlator and VGOS Sessions
L. La Porta, W. Alef, S. Bernhart, A. Müskens, H. Rottmann, T. Schüler, J. Wagner

Abstract The MPIfR/BKG correlator in Bonn has along experience in processing IVS sessions and it has
been preparing for handling broadband experiments foryears. We would like to give an estimate of our current
capabilities for a sustainable VGOS duty cycle.

Keywords VGOS · Correlation

1 Introduction
The Bonn correlator is operated jointly by the Max
Planck Institute for Radio Astronomy (MPIfR) in
Bonn and by the Federal Agency for Cartography andGeodesy (Bundesamt für Kartographie und Geodäsie,
BKG), with the support of the Institute of Geodesy andGeoinformation (IGG) of the Bonn University. The
MPIfR hosts the correlator facility and shares with the
BKG the costs of the cluster, of most of the staff andof the Internet connectivity. The IGG contributes tothe connectivity of the cluster and pays one memberof the geodetic staff. Since January 2017 the personnel
responsible for the correlation of geodetic sessions isemployed by the BKG via a private contractor, theReichert GmbH.
An extensive description of the Bonn correlator
personell and activities, as well as technical details forexample concerning the software tools exploited forpost-processing may be found in the IVS Biennial Report (La Porta et al., 2019). Here we will focus on theinformation relevant for our considerations.
The Bonn correlator is a Distributed FX software
correlator (Deller et al., 2011). It is installed on a High
Performance Computing (HPC) cluster (see Fig. 1),
which consists of:• 68 nodes with 20 compute cores each,• three head nodes for executing more correlations
in parallel,• 56 Gbps Infiniband interconnect between all
nodes,• 1.5 PB of disk space organized in RAID units andcombined in a BeeGFS parallel cluster file system,• 15 Mark 5 playback units, and 9 Mark 6 playback
units each with four bays (see Fig. 2).

Laura La Porta · Simone Bernhart
Reichert GmbH, Hittofstraße 26, DE-53129 Bonn
Walter Alef · Helge Rottmann · Jan Wagner
Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69,
DE-53121 Bonn
Arno Müskens
Institut für Geodäsie und Geoinformation der Rheinischen
Friedrich-Wilhelms Universität Bonn, Nußallee 17, DE-53115
Bonn
Torben Schüler · Laura La Porta · Simone Bernhart
Geodätisches Observatorium Wettzell, Bundesamt für Kartographie und Geodäsie, Sackenrieder Str. 25, DE-93444 Bad Kótzing(Correspondence: laporta@mpifr-bonn.mpg.de)Fig. 1: New HPC cluster at MPIfR seen through a glass wall.

103

104

Fig. 2: View of the Mark 5 and Mark 6 units through a glass wall.

The HPC cluster is connected to the Internet
through two 1-Gbit lines.

2 Our experience with EU-VGOS test
sessions
In March 2018 - upon an initiative of W. Alef - theBonn Correlator Center started a collaboration with thethree European stations of Wettzell, Onsala and Yebes,
equipped with both standard S/X- and broadband systems, to carry out a European VGOS Proof-of-Concept
study (EU-VGOS). We refer you to the Proceeding of
W. Alef for an exhaustive report about the project andthe results achieved so far. Here we will restrict our
discussion mainly to the aspects related to data transfer
and storage.
The aim of the project is to verify the processing
chain for VGOS experiments end-to-end, from thescheduling to the geodetic analysis of the derived
observables. All parties are learning about and investigating the various aspects of the project, fromthe more technical ones, as system settings and data
recording at the station, to data decoding and correlation, and finally to the post-processing of the data,
i.e. to the fringe-fitting. This is necessary in light of
the forthcoming IVS-VGOS era. In particular, most of
the European stations have different back-end systems
w.r.t. the American sites, and they must rely mostly
on their own resources to debug their systems withthe support of the correlator and of the DBBC team in
Bonn. As an example, these first test sessions revealed
that the VDIF multithreaded files generated via VGOS
broadband systems sometimes show anomalies.

La Porta et al.

Namely, the threads are not correctly interleaved intime: for each time tag there should be all threads
present in the file, whereas some threads appear witha certain delay w.r.t. the others. As a result DiFX’s
decoding buffers can overflow, thus leading to data
loss. The percentage of correlated data decreased by
70 % in the worst cases we experienced. The problem
can be circumvented by reordering the threads in theraw data file and merging them into a single-thread,but that extra-step costs time and storage space. As
this work-around is time-consuming and requires
additional storage space, it is unsuitable for routine
operations. J. Wagner is currently implementing a fix
for the issue.
Test observations were performed shortly before
the IVS VGOS-Test (VT) sessions by adopting thesame frequency set-up, thus minimizing both the effort for the participating stations and the risk to jeopardize the official IVS sessions. Dual polarization observations were carried out in four 512 MHz wide bands at
about 3 GHz, 5 GHz, 6 GHz and 10 GHz. In each band8 channels of 32 MHz were sampled with 2-bits, thus
providing an acquisition rate of 8 Gbps. The test sessions lasted 4 hours and included about 150 scans witha typical duration of 30 seconds, but also targeted 3-4strong calibrators for which longer scans of about 120
seconds were performed. The amount of data recorded
at each station was of about 6 TB. Assuming to use themaximal data transfer rate currently available between
each stations and the correlator, i.e. 600 Mbps, it would
take between 1.5 to 4.5 days to complete the transfersof the raw data to Bonn. In practise, VGOS is not yet
in the production phase in Bonn and we could not dedicate our internet connection entirely to the project, sothat it took on average 2 − 4 weeks to fetch all data.
Due to the above mentioned issues with multithread vdif data, we first have to convert the files into
single-thread data. For 6 TB of data that process takes
about half a day on our cluster. The correlating time of
one test session amounts to 2 − 3 hours: the correlator
needs on average 1 − 1.5 minutes to complete one
job (or equivalently one scan). We currently assume
one day for fringe-fitting and DB-creation, but it
could become shorter as we collect experience inhandling the post-processing procedures. In the bestcase scenario (i.e. bandwidth reserved for runningtransfers in parallel) we may generate a database
within 3.5 days after the observations. In a more

VGOS at the Bonn Correlator

realistic scenario - geodesy is not the only nor the main
activity at the Bonn correlator - we would transfer thedata of the stations one after the other, but we would
start converting as soon as we get the data and we
could complete post-processing within 6 days after theobservations.

3 Future IVS-VGOS intensive sessions
For 2019 the IVS plans to start VGOS intensive sessions on a regular basis. One option would be to schedule two stations equipped with VGOS systems, for example Wettzell and Kokee, for weekly one hour sessions. If we stick to the frequency set-up currently used
in VT sessions and adopt a typical geodetic schedule,
then we would have 15 second on source followed by
30 seconds slewing time, thus leading to about 80 scans
per session for a total of 1.2 TB of data per station. If
we reserved the bandwidth to the transfers of the raw
data, as we usually do for the INT3 sessions on Mondays, and performed the transfers with a rate of 800
Mbps for both stations, then it would take about 200
minutes to fetch all data. On the Bonn HPC cluster it
would take 1 hour to correlate the experiment and a
few hours for post-processing and for generating thedatabase. In conclusion, if observations were carriedout at 7:00 UT we may deliver the dabatase within one
working day.

4 Future IVS-VGOS 24-hour sessions
As an exercise we would like to extrapolate these latency times to 24-hour sessions with a larger number ofparticipating stations, as in the case of the VT sessions.
It is straightforward to estimate how long it will taketo fetch the raw data with a 2 Gbps line and how muchstorage space will be needed. The storage capacity inBonn would be sufficient for the time being. There arevarious factors, which may affect the correlator performance. For example, the playback rate, but that is
not going to be an issue in Bonn, given that we havea 56 Gbps interconnection between the nodes. Amongthe various factors which may affect the correlator performance, the only limiting one could be the computing
capability. On a HPC with the same characteristics as

105

in Bonn the computing time increases linearly with theamount of data to be correlated (H. Rottmann, private
communication).
Let us consider a 24-hour geodetic session (30 seconds on source, for a total of about 580 scans) with 6
stations and an acquisition rate of 8 Gbps. Under these
conditions 16 − 17 TB of data would be recorded ateach antenna. With the present internet connections we
could carry out at most 3 transfers at 600 Mbps in parallel (one has to note that a few stations have larger
bandwidth at disposal) therefore it would take approximately 4 days per station to fetch the raw data and aminimum of 10.5 days to fetch all data for correlation.
If stations opted for sending Mark6 modules instead, itwould take 1 − 2 weeks for the data to reach the correlator, based on Haystack’s experience. Moreover, it
would imply having a budget for shipping cost, which
is currently not the case for the Bonn correlator, atleast for geodesy. If we completed the post-processing
within 2 days, then in the best case scenario we would
submit the database within 10 − 11 days after observations, although based on Haystack’s experience with
the IVS-VT sessions a month would seem a more realistic estimate.
Nowdays the bottle neck in the pipeline is without any
doubts the transfer of raw data to the correlation center.

5 Conclusions and outlook
According to the IVS Strategic Plan for the Period
2016–2025 (Nothnagel et al. 2016), geodetic VLBI
should transition from S/X systems to VGOS systems
during this decade. The progress is slower than foreseen, for example only 6 instead of 16 VGOS stations
are operational at present. Moreover, the difficulties
related to data transfers and storage are such that so
far only bi-weekly sessions with a low acquisition rate
have been conducted on a regular basis within the IVS
activities. In recent years new correlation centers havebeen founded and started cooperating with the IVS,
however the Bonn correlator is still a main actor on the
IVS scene and matches VGOS requirements at least interms of computing capabilities. It can therefore serveas test bed to understand the pace at which VGOS production may begin.
We considered the initial VGOS observing schedule with daily 1-hour sessions. Based on our experience106with the EU-VGOS test sessions, our correlator centercan deliver the database of a VGOS intensive session
with the current set-up within 24-hour from observations, thus matching the timeliness achieved for INT3.
We underline that this is far from the IVS final goal as
laid out by the Board of Directors in 2016, which is to
produce such a database every 3-hour and with both amuch larger network and a higher acquisition rate.
In the case of 24-hour sessions the latency time increases to 10 − 11 days already under these initial conditions, i.e. 6 stations and a 8 Gbps acquisition rate.
A feasable production cycle would be of roughly a couple of weeks for a correlator with similar characteristics as in Bonn. One would therefore need at least 15
correlators to share the work load to carry out observations 24/7.
The main issues for VGOS regular observations are
the transfer and the storage of the data both at the stations and at the correlator end. The costs for internet
connections are still rather expensive, although the situation may vary significantly from one country to another. Stations would need at least a 2 Gbps line, whilst
correlators should have at least 10 Gbps to allow etransfer of the data. Stations should be equipped with

La Porta et al.

local buffering systems (i.e. using flexbuff for recording) or they should purchase twice as many modules
as those needed for the sessions in one week. Correlators would also need quite some extra storage spaceand new agreements should be stipulated between stations and correlators to cover those costs. Countries
that build an antenna to participate in geodetic sessions
should also include in the budget some funding for thelogistics to make the correlation of the collected data at
all possible. Ideally, they should also contribute to thecosts of the correlation centers as well.

References
Deller A T, Brisken W F, Phillips C J, et al. (2011) DiFX-2:
A More Flexible, Efficient, Robust, and Powerful Software
Correlator, PASP, 123, 275–287
Nothnagel A, Behrend D, Bertarini A, et al. (2016) Strategic
Plan of the IVS for the Period 2016-2025. In: D. Behrend,
K. D. Baver, K. L. Armstrong (eds.): IVS 2016 General
Meeting Proceedings, NASA/CP-2016-219016, 3–12
La Porta L, Alef W, Bernhart S, et al. (2019) The Bonn Correlation Center, IVS 2017+2018 Biennial Report, in press

The EUropean-VGOS Project
W. Alef, J. M. Anderson, S. Bernhart, P. de Vicente, J. González Garcı́a, R. Haas, L. La Porta, I. Martı́ Vidal,
A. Müskens, A. Nothnagel, C. Plötz, H. Rottmann, T. Savolainen, T. Schüler, D. Small, J. Wagner

Abstract In Spring 2018 the Bonn correlation centre started a collaboration with the three European stations of Wettzell, Onsala and Yebes, equipped withboth S/X- and broadband systems, to perform VGOSWalter Alef · Helge Rottmann · Jan Wagner · Tuomas Savolainen
Max Planck Institute for Radio Astronomy, Auf dem Hügel 69,
DE-53121 Bonn, Germany

like test sessions. The aim is to verify and develop further the processing chain for VGOS experiments endto-end, from the scheduling to the analysis of the derived observables. We will present the current status of
the project.

Keywords VGOS · VLBI broadband observations

Simone Bernhardt · Laura La Porta
Reichert GmbH/BKG, Hittorfstr. 26, DE-53129 Bonn, Germany
Arno Müskens · Axel Nothnagel
Institute of Geodesy and Geoinformation, University of Bonn,
Nußallee 17, DE-53115 Bonn, Germany
Pablo de Vicente · Javier Gonzaléz Garcı́a · I. Martı́ Vidal
Observatorio de Yebes (IGN), Cerro de la Palera S/N, Yebes,
Guadalajara, Spain
Christian Plötz · Torben SchülerGeodätisches Observatorium Wettzell, Bundesamt für Kartographie und Geodäsie (BKG), Sackenrieder Str. 25, DE-93444 Bad
Kötzting, Germany
Rüdiger Haas
Chlamers University of Technology Onsala Space Observatory,
SE-439 92 Onsala, Sweden
James M. Anderson
Technical University of Berlin, Institut für Geodäsie und Geoinformationstechnik, Straße des 17. Juni 135, DE-10623 Berlin,
Germany, also at: GFZ German Research Centre for Geosciences, Department 1, Geodesy, Telegrafenberg, DE-14473
Potsdam, Germany
Tuomas Savolainen
Aalto University Department of Electronics and Nanoengineering, PL 15500, 00076 Aalto, Finland, also at: Aalto University Metsähovi Radio Observatory, Metsähovintie 114, FI-02540
Kylmälä, Finland
Des Small
Joint Institute for VLBI ERIC, Oude Hoogeveensedijk 4, NL7991 PD Dwingeloo, The Netherlands(Correspondence: alef@mpifr-bonn.mpg.de)

1 Motivation and aims
The main motivation for starting a scientific investigation on VGOS is the will to speed up the transition from classical geodetic VLBI to broadband observations. According to the initial IVS strategic plan,
VGOS production should have started already by theend of 2017, but the complexity of the project and thelack of manpower led to a long delay in implementing production VGOS observations. VGOS telescopes,
some of which were inaugurated as early as 2013, arestanding idle most of the time much to the chagrin of
their funding agencies. So VGOS antennas are available and are ageing, while telescope crews still lackpractice in VGOS observing.
In 2015 the Bonn cluster was upgraded following
the IVS-VGOS correlation plans of Petrachenko et al.
(2014), which foresaw an increasing demand that has
not yet become real as of 2019. The cluster will be
old in 2020 and should be renewed in 2020 to 2022.
Only recently IVS-VGOS data have been made available, which is necessary not only for training correlator
personnel, but also for studying the steps in data reduction after correlation.
Since 2015 bi-weekly test sessions have been carried out by the IVS under the lead of the MIT Haystack
107

108

group, which developed a path for observing, correlating and fringe-fitting of VGOS data (see e.g. Cappallo2014). Their approach exploits the “pseudo-Stokes-I”(Intensity), which ignores instrumental and source polarisation, as well as changes and differences between
the position of the peak in total and in polarised intensity. From astronomical observations it is known
that the angle of the source polarisation can vary more
rapidly than total intensity. It is also known that instrumental polarisation leakage leads to delay errors.
Investigations of Anderson and Xu (2018) haveshown that the effects of source structure on the delays have been underestimated and will affect VGOS
to a larger extent due to the expected reduced noise insuch data. The whole problem is aggravated by variation of the source structures and the position of thecentroid which can change with time. The position of
the centroid as a function of frequency is another relevant source of systematic errors in VLBI broadband
data.
Unfortunately no scientific investigation exists up
to date, which studies the various effects and their contributions to the geodetic residuals of VGOS data.
Wideband astronomical VLBI data as recorded for
the Event Horizon Telescope (EHT) have triggered
new software efforts for polarisation conversion andfor fringe-fitting. While VLBI observations have been
performed with circular polarisation, ALMA, a key element of the EHT, can only deliver linear polarisation. It is therefore necessary to convert ALMA datafrom linear to circular polarisation basis (Martı́-Vidal
et al., 2016), which is done after correlation. Similarly,
VGOS receivers produce linear polarisation, whereas
geodetic legacy S/X systems measure circular polarisation.
The standard fringe-fitters (FF) cannot handle
wideband data, because they do not take properly into
account the effects of ionosphere, source structure andpolarisation. A new fringe fitting task for broad andnon-contiguous frequency bands, as well as correction
for dispersive delays is being developed for the astronomical CASA package (van Bemmel et al., 2019). So
there are new options for fringe-fitting geodetic data
which should be explored. Some of the astronomical(global) FFs can take the source structure as a natural
input, which makes them good candidates also for
geodesy involving source structure corrections.
To the authors it is clear that in order to reach 1 mm
positional accuracy, all steps of VGOS observing andAlef et al.

data reduction have to be optimised. That will require a
broad range of expertise and sufficient manpower. The
whole geodetic/astronomical community should ideally join forces, given that astronomy is also moving toan era of broadband observations and shares common
open issues with geodetic VLBI. The DiFX software
correlator community is an example of how successful
such an open collaboration can be.

2 Observations and correlation
The first test sessions were dedicated to test the performance of the instruments. Having a minimum of 3
stations allows any problems identified to be isolated
at a specific station. The three participating stations areequipped as follows:• ONSA13NE (ONSA13SW became operational
only recently): 13.2 m antenna, QRFH receiver,
VLBI back-end DBBC3 with flexbuff recording• WETTZ13S (WETTZ13N not equipped withbroadband receiver yet): 11-feed receiver, VLBI
back-end 2 DBBC2 with Mark6 recording• RAEGYEB: 13.2 m antenna, QRFH receiver,
VLBI back-ends are 4 RDBEG with Mark6
recording
The EU-VGOS sessions have been scheduled by using
both SKED and SCHED and include standard geodetic
sources (time on source ∼ 30 sec) and at regular intervals strong calibrators (integration time ∼ 120 sec) thatcover a wide range of parallactic angles during the observation. Good parallactic angle coverage of a calibrator is necessary for accurate polarisation conversion.
The observations last 4 hours and include sources withhigh and low fractional polarisation in order to test thepolarisation leakage calibration method.
So far we have adopted the same frequency setup
as used in the IVS-VT sessions — four bands with dual
linear polarisation:• 3000.40 MHz – 3480.40 MHz• 5240.40 MHz – 5720.40 MHz• 6360.40 MHz – 6840.40 MHz• 10200.40 MHz – 10680.40 MHz
In each band we sample 8 channels of 32 MHz bandwidth at a sample rate of 64 MS/s using two bits, thus
resulting in a data rate of 8 Gbit/s. Data are recorded
either using Flexbuff (JIVE) or on Mark6 modules

EU-VGOS

in VDIF1 format. The stations generate multi-thread
VDIF data in slightly different flavours:• Onsala (real data) – 1 VDIF file per scan with 8
threads, 8 channels per thread• Wettzell (real data) – 1 VDIF file per scan with 4
threads (1 for each band), 16 channels (8 channels
x 2 linear polarisations) per thread• Yebes (complex data) – 1 VDIF file per scan with
4 threads, 16 channels per thread
The recorded data are later “e-transferred” to the Bonncorrelator via the Internet.
The file-based correlation and the backend setup
have hit a few corner case issues in DiFX correlation.
The main issue is thread-clumpiness inside recordings.
The specifications of the recorded data format andits multi-threaded multi-channel capability allow great
flexibility in the time sequencing of data frames inside
one file. In EU-VGOS test experiments, station backends and recorder setups have produced VDIF files thatadhere to the specifications, but that contain frames ofindividual threads in long data bursts rather than in aclean round-robin order. This “clumpiness” conspires
against DiFX and its buffer-based VDIF decoding approach. High data loss (low visibility data weights) areseen when the burst length exceeds the preset DiFX
VDIF decode buffer size. Curiously, the problem persists even when threads of a multi-threaded VDIF fileare extracted into single-thread VDIF files that arethen correlated simultaneously in DiFX via its “multidatastream” support.
Conversely, the low data weight issue does not occur when the original Mark6 scatter(-gather) fragment
file sets (usually not available via e-transfer) are used
as input for correlating a scan. The difference is likely
due to the different VDIF reading path that DiFX uses
for “scattered” Mark6 versus “gathered” file based correlation.
The above problem has also been reported by MIT
Haystack. At Bonn the issue is worked around by a preprocessing step prior to correlation. The multi-threaded
multi-channel VDIF files of all stations are converted
into single-threaded multi-channel files using DiFX
utility ”vmux” configured for a very large buffer size (≥800 MB). This recovers visibility data weights from aprevious worst of ≤20 % to generally ≥99 %. However,
due to the overhead at the correlator such a prepro1 VDIF specifications, cf. https://vlbi.org/vlbi-standards/vdif/

109

cessing step is not ideal. To omit the VDIF preprocessing step, development of improved support for generalmulti-threaded VDIF was also welcomed by the NRAO
and is in progress at Bonn MPIfR. An initial implementation is being tested.

3 Data analysis
The conversion of linear polarization into circular is
performed using the PolConvert algorithm (Martı́Vidal et al., 2016). The conversion process needs to be
fed with the phase-gain difference and the amplitudegain ratio between the two linear polarizers (X andY) of each antenna. These quantities can be estimatedusing the Global Cross-Polarization Fringe Fitting(GCPFF) algorithm, as implemented in PolConvert,
using a scan of a calibrator source (ideally, a sourcewith either a low fractional linear polarization and/or awide parallactic-angle coverage in the observations).
Before running the GCPFF, we applied an initial estimate of the phase-gain difference between polarizers,
based on the values of the phasecal tones found for X
and Y at each integration time. The relative gain amplitudes were also estimated from the autocorrelations
at each polarizer (after filtering the peaks due to thephasecal tones).
Then, we selected a strong calibrator (3C 84) andsolved for any additional X/Y relative phases that could
remain (after the phasecal corrections), as well as for
additional X/Y amplitude ratios. These additional relative gains (both in phase and amplitude) could becaused, for instance, by different phasecal cabling to
the two polarization components, or to the particularsof the signal path of each polarization channel.
These additional X/Y relative phases (which are
added to the phasecal differences between X and Y)
and X/Y relative amplitudes (which are applied on
top of the autocorrelation ratios) are shown in Fig. 1.
On the one hand, the X/Y phase difference computedby the GCPFF can be roughly modeled as one single multiband delay across the whole EU-VGOS frequency coverage. On the other hand, the amplitude ratios show different values for each band and can departsubstantially from unity (hence introducing a large instrumental ellipticity, if they were not taken into account in the conversion).

110

Alef et al.

Fig. 3: Circular polarisations (RR, LL, RL, LR) amplitudes ofall sampled channels for a scans on 3C84.

Fig. 1: X/Y relative phases (top) and amplitudes (bottom) for Oe(ANT. 1), Ws (ANT. 2) and Yj (ANT. 3).

3.1 First results
Fig. 2 and Fig. 3, respectively, show the amplitudes of
all correlation products, for a scan of a strong calibrator source, before (i.e., XX, XY, YX and YY) and after(i.e., RR, RL, LR, LL) conversion from linear to circular, as a function of frequency channel (each increasing
with frequency). It can clearly be seen how most of thepower is coherently injected into RR and LL.
In Fig. 4, we show the antenna gains derived for thesame calibrator scan using the standard Global Fringe
Fitting (GFF) algorithm. The GFF has been applied to
the Stokes I fringes in each independent IF. The phasecal tones (which are now the same for the R and L
channels) have been applied before the GFF. As it canbe seen in the figure, all gain quantities (phase, delay
and rate) can be properly connected among the different EU-VGOS bands, hence showing the possibility ofFig. 2: Linear polarisations (XX, YY, XY, YX) amplitudes of all

sampled channels for a scans on 3C84.

Fig. 4: Results of the GFF applied to the Stokes I fringes of ascan on 3C 84, obtained after polarisation conversion.

performing a consistent multi-band analysis over all
the VGOS frequency coverage.
The GFF gains can be applied to all four polconverted correlation products, in order to perform an image deconvolution in full polarization. We have performed a multi-frequency synthesis (MFS) image deconvolution (Sault and Wieringa, 1994) using all scansof source 3C 279. The preliminary imaging results areastonishingly good, as can be seen in Fig. 5. White
contours show the brightness distribution of Stokes I,
while the red contours show the I residuals after subtracting a centered point source. The red contours arewell aligned into the same direction as the known jet of
3C 279, hence indicating that EU-VGOS is resolving
the source. The orange raster plot shows the brightness
distribution in linear polarization, which is shifted fromthe I peak just in the same direction of the jet. The polarized brightness, polarization angle, and its peak shiftroughly agree with published results from dedicatedEU-VGOS

Fig. 5: Image of 3C 279 obtained from the polconverted (andfringe-fitted) EU-VGOS data.

VLBI observations of this source at other frequencies(e.g., Rani et al., 2018).

111

instrumental delays between the X- and Y-polarisation
components and their leakages. Moreover, we will
investigate how the polarisation leakage changes withfrequency and with the targeted source. Last but notleast, we will check the RFI situation for each station.
All collaborating parties, stations, correlator andanalysts, are gaining insights in the various aspects ofthe project, from the more technical ones, as systemsettings and data recording at the stations, to the elaboration phases, including data decoding and correlation,and finally to the post-processing of the data. As mentioned in the previous section, we also plan to develop
and test against each other alternative FF approaches
for processing VGOS data.
Our preliminary results show the potential of VLBI
broadband data. We are aware of the huge amount ofwork necessary to accomplish all our goals and wewelcome experts in the VLBI community and other
VGOS telescopes who wish to cooperate with us tomake VGOS production a reality as fast as possible.

4 Conclusions and outlook

References

Both astronomy and geodesy are transitioning to a newera of broadband VLBI observations. That opens new
frontiers for both fields of research, as well as newchallenges on the way to the results. The EU-VGOS
project answers the urgent need to further investigate
some aspects related to the new technology and to themethodology in processing and analyzing the data.
Note that the European stations have different backend systems w.r.t. the American sites, therefore theymust rely on their own resources to debug them. The
correlation constitutes an expensive but powerful diagnostic tool, thus allowing to verify the station performance. We adopt different observational strategies forour sessions, thus allowing us to focus on the various
aspects to be tested. We need to characterize the bandpass response of the instruments and how it changes
with time, and to verify the performance of the pulse
calibration system. We will monitor over many months
the stability of the gain (amplitude and phase) in time,
as well as its frequency dependency.
The wideband receivers use linearly polarized
feeds, so that the baseline correlations are highly
mixed among the parallel and cross-hand polarization
terms due to the earth geometry. We will determine theAnderson J M, Xu M H (2018) Source Structure and Measurement Noise Are as Important as All Other Residual
Sources in Geodetic VLBI Combined. J Geophys Res (Solid
Earth), 123 https://ui.adsabs.harvard.edu/#abs/2018JGRB.
.12310162A
Cappallo R J (2014) Correlating and Fringe-fitting Broadband
VGOS Data. In: D. Behrend, K. D. Baver, K. L. Armstrong (eds.): IVS 2014 General Meeting Proceedings, Science Press (Beijing), ISBN 978-7-03-042974-2 https://ivscc.
gsfc.nasa.gov/publications/gm2014/019 Cappallo.pdf
Martı́-Vidal I, Roy A, Conway J, et al. (2016) Calibration of
mixed-polarization interferometric observations. Tools forthe reduction of interferometric data from elements with linear and circular polarization receivers A&A, 587, 143
Petrachenko B, Bertarini A, Alef W, et al. (2014) VGOS Data
Transmission and Correlation Plan, Internal Report, VGOS
Project Executive Group (VPEG), Version: November
18, 2014, https://ivscc.gsfc.nasa.gov/technology/vgos-docs/
VGOS DataTransmissionCorrelation Plan 141118.pdf
Rani B, Jorstad S G, Marscher A P (2018) High-resolution polarization imaging of the Fermi blazar 3C 279. 7th Fermi
symposium proceedings (Fermi 2018), PoS(IFS2017)020
Sault R J, Wieringa M H (1994) Multi-frequency synthesis techniques in radio interferometric imaging. Astronomy and Astrophysics Suppl., 108, 585
van Bemmel I, Small D, Kettenis M, et al. (2019) CASA on thefringe: VLBI data processing in the CASA software package. Proc. 14th European VLBI Network Symposium & User
Meeting (EVN 2018), PoS(EVN2018)079

Implementation of a Geodetic Path at the JIVE Correlator
M. E. Gómez, M. Kettenis, P. Charlot, R. M. Campbell, A. Keimpema

Abstract This paper reports on the progress towards
the implementation of a complete geodetic path for the
EVN Software Correlator at JIVE (SFXC). It is conducted as part of the JUMPING JIVE project funded by
the Horizon 2020 Framework Programme of the EU.
JUMPING JIVE is dedicated to enhance the position of
JIVE and the European VLBI Network (EVN) within
the future of radio astronomy. This includes implementation of new capabilities, among which is the possibility to correlate geodetic-type experiments and export
them in a standard fashion so that they can be further
processed by the usual geodetic software packages.
The implementation of this new capability requires (i)to make SFXC able to handle complex geodetic-likeschedules with sub-netting, and (ii) to incorporate total
quantities and measured phase-cal values in the data
provided to the users. To facilitate post-processing, it
was also decided to convert the correlator output tothe standard geodetic Mark4 format. All such developments are now complete. To test the implementation,
we have reprocessed IVS session R1872 and compared
the output from SFXC with that obtained at the DIFX
correlator in Bonn, where the session was originallyprocessed. The methodology is explained here and partial results of the comparison are given. These indicate
a 5.5 ps wrms for the Total Multiband Delay difference
between the two correlators.

1 Introduction
JUMPING JIVE is the acronym for Joining up
Users for Maximizing the Profile, the Innovation andNecessary Globalization of JIVE, a project fundedby the European Union’s Horizon 2020 programme.
The project1 is divided into ten work packages (WP)
that cover various aspects from dissemination totechnical developments and future science with theEuropean VLBI Network (EVN). In this paper we areconcerned with WP6 activities which have to do with
the implementation of full geodetic capabilities at the
EVN software correlator at JIVE (SFXC). This meansthat the correlator should be able to:
1. Correlate data with proper handling of geodetic
sessions which are scheduled with sub-netting;
2. Attach the correlator model to the correlator output;
3. Attach phase-calibration information to the correlator output;
4. Provide correlator output in the appropriate format
for further geodetic post-processing.
From the correlator output, an analysis center shoudthen be able to:
5. Post-process and export the data.

Mark Kettenis · Robert M. Campbell · Aard Keimpema
Joint institute for VLBI-ERIC, Dwingeloo, The Netherlands

The items listed above constitute also the steps ofthe procedure followed to validate the whole implementation at JIVE. The first step was accomplishedat the end of 2017: one hour of an IVS-R1 session(which included sub-netting) was successfully correlated (Colomer et al., 2019). Steps 2 to 4 were also accomplished and are described in Keimpema and Kettenis (2019).

(Correspondence: maria.gomez@u-bordeaux.fr)

1 https://jive.eu/jumping-jive

Keywords JUMPING JIVE · EVN · VLBIMaria Eugenia Gómez · Patrick Charlot
Laboratoire d’Astrophysique de Bordeaux, Pessac, France112

Geodetic path at the JIVE Correlator

113

vided by the Bonn Correlator Center for IVS-R1872.
They also provided us with post-processed data and thevgosDB file version 1 so that we could check our results against theirs. The comparison was done at thelevel of vgosDB files. The second stage of the validation comprised post-processing JIVE-correlated data
for that session and compare our results with respect tothose obtained in Bonn.

Fig. 1: Stations involved in the IVS-R1872 session.

In the following, we will focus on step 5. For that
purpose, a whole 24-hour IVS session, IVS-R1872(held on December 10, 2018) was selected. This experiment involved eight IVS stations (Fig. 1) and observed
a total of 1069 scans.

2 Methodology
2.1 Correlation
IVS-R1872 was originally correlated with the DIFX
correlator in Bonn. For the purpose of the project, it
was also subsequently correlated at JIVE with SFXC.
Both correlator outputs were exported into the standard
geodetic Mark4 format. Additionally, the Bonn correlator center further exported the data into vgosDB format (version 1), which is the newest and current format
for geodetic datasets, after post-processing. A difference in the processing is that SFXC used a delay model
based on CALC 10 whereas the delay model used with
DIFX was CALC 11.

2.2 Post-processing and data export
In order to check the Mark4 implementation and postprocessing, we devised a validation procedure in twostages. The first stage comprised checking our ability
to find fringes and to produce vgosDB file version 1.
This was done using the correlated Mark4 files pro-In the post-processing, we applied exactly the same
control file as that used at the Bonn Correlation Center because there was no reason to introduce changes
when processing the data correlated at JIVE. We used
Fourfit (HOPS 3.18 rev 2251) for that purpose andvgosDbMake-0.4.3 to transform the data into vgosDB
format. The selected version of each software was notarbitrary: it was the same as that employed in Bonnin order to avoid potential differences due to software
version or other issues. Netcdf library and Octave tools
were used to extract and plot the data.
According to Corey and Titus (2012), differencesat the ps level between results from the two correlators
should be expected. Because of differences in the correlation process and correlator architecture, the comparison was not straightforward. The time of each observation is tagged according to what is called the Fourfit Reference Time (FRT) which may differ from one
correlator to the other, due to differences in how thecorrelators search for the first valid input data for eachscan. This situation causes natural discrepancies in the
Total Multiband Delay (TOTMBD) just because we are
evaluating this quantity at different FRTs. For this reason, in the section below, we just show results concerning those observations that end up with the same FRT
in Bonn and JIVE.

3 Results
Figure 2 shows results after comparing the vgosDB filesent by Bonn and our own vgosDB file obtained from
Bonn correlated data (stage 1). The plots are for the
TOTMBD and Signal to Noise Ratio (SNR) quantities in X-band. There are no appreciable differences
between the two datasets at the 15-digit significancy
level for any observation. This is replicated for S-band
and for all the other observables like e.g. single-banddelays. This initial check guarantees that no bias will

114

Fig. 2: Differences in TOTMBD and SNR ratios wrt Bonn ob-

tained after comparing the original and reproduced vgosDB files
from Bonn for IVS-R1872 session.

come from local implementation or software version
differences.
In order to reproduce the previous analysis, but
now comparing the output of both correlators, we took
all those observations that have the same FRT anda quality code greater than zero and we plotted the
TOTMBD differences and SNR ratios for this subset of data (Fig. 3). There are 3462 of such observations within a total of 5826 observations in the session. Statistics of the TOTMBD differences indicate a
5.5 ps wRMS (weighted RMS) with all values below
50 ps and 80 % of them below 5 ps. In the case of
the SNR ratio, the average value is 0.998, which meansthat there is no bias between SFXC and the Bonn DiFX
correlator. The magnitudes of the differences between
the two correlators, for the TOTMBD and SNR quantities, are according to what is expected (see Coreyand Titus, 2012) and confirm that the geodetic pathis correctly implemented on SFXC. The correspondingvgosDB file for IVS session R1872 is the first dataset
produced in standard geodetic format after correlation

Gomez et al.

3: Differences in TOTMBD and SNR ratios(S NR JIV E /S NRBonn ) obtained after comparing the vgosDB
files produced by SFXC and the Bonn DiFX correlator for IVS
session R1872. The comparison is limited to those observations
that have the same FRTs.
Fig.

with SFXC. Further study is being done on the remaining observations (i.e. those that do not have the same
FRTs) in order to complete comparisons for the entire
session.

4 Conclusions
We have shown that the EVN Software Correlator at
JIVE (SFXC) has the capability to correlate data froma standard geodetic session and its output can be fully
analysed with the most common geodetic tools. Using
data correlated through SFXC we were able to produce the first dataset in the vgosDB standard geodetic format. SNR ratios and TOTMBD differences between SFXC and the Bonn DiFX correlator were analysed for those observations that have the same FRTs
and are at the anticipated level. The comparison for
the rest of the observations (those that do not have theGeodetic path at the JIVE Correlator

same FRTs) will also be accomplished after devising aproper scheme in order to fully complete the work.
Acknowledgements The authors would like to thank Laura La
Porta and the Bonn Correlator Center for providing us with thecorrelated and post-processed data of the IVS-R1872 session as
well as all the auxiliary files. We are also grateful to Laura La
Porta for useful discussions. This research received funding fromthe European Union’s Horizon 2020 Research and Innovation
Programme, under grant agreement No. 730884.

115

References
Colomer F, Campbell R, Kettenis M, et al.(2018) Geodetic capabilities of the JIVE SFXC correlator. In: K. L. Armstrong,
K. D. Baver, D. Behrend (eds.): IVS 2018 General Meeting
Proceedings, NASA/CP-2019-219039, 117–120
Corey B, Titus M (2012) Multiband delay differences between Mk4 hardware and DiFX software correlations. MIT
Haystack Observatory memorandum, 2012 September 18.
Keimpema A, Kettenis M (2019) Recent technical developments at JIVE. Presentation at 24th EVGA Working Meeting, Gran Canaria, www.oan.es/evga2019/EVGA2019 PDF/
O115 EVGA2019 Keimpema.pdf

Activity Report on the Asia-Oceania VLBI Group (AOV)
T. Wakasugi

Abstract The Asia-Oceania VLBI Group for Geodesy
and Astrometry (AOV) was established in 2014 asa subgroup of the International VLBI Service forGeodesy and Astrometry (IVS) in order to foster
regional collaboration of VLBI. The AOV has beencoordinating regular VLBI observing sessions since2015. The total number of sessions amounts to 30
at the end of 2018, and 19 stations in five countries
have participated in these sessions. The Geospatial
Information Authority of Japan (GSI) has actively
involved in the AOV as not only an observing station
but also a scheduler and correlator. This talk willsummarize activities of the AOV since its launch.
Fig. 1: The AOV logo.

Keywords AOV

1 Introduction
As you already know, the Asia-Oceania (AO) regionis highly dynamic in geophysics and climate, with alarge number of destructive earthquakes, tsunamis, typhoons, and cyclones. To enhance disaste resilience
for the region, determination of the geodetic reference
frame is essential through precise Earth observations
and better understanding of tectonic plate motion, atmospheric variations etc. VLBI components in the AO
region are rapidly glowing compared to IVS launch.
More international collaboration is important to takeTakahiro Wakasugi
Geospatial Information Authority of Japan 1 Kitasato, Tsukuba,
Ibaraki 305-0811 Japan(Correspondence: wakasugi-t96kg@mlit.go.jp)

full advantage of components in the region. In addition, momentum for rise of the position in the VLBI
community is glowing.

To realise those ambition, some asian researchers
discussed the idea of regional collaboration on geodetic
and astrometric VLBI in Asia during the 21st EVGA
Meeting in Finland in 2013. After that, the idea wasextended to oceanian region for more effective cooperation. The foundation of a regional VLBI community
for Asia-Oceania region was agreed at the 30th IVS Directing Board Meeting in September, 2013. The group
was named as Asia-Oceania VLBI Group for Geodesy
and Astrometry and its acronym was called AOV (Figure 1) (Kurihara et al., 2015).
116

AOV Report

117

2 Status of the AOVThe kick-off meeting was held at Shanghai in conjunction with the 8th IVS General Meeting and Termsof Reference was discussed and finalized. Jim Lovell
from University of Tasmania (UTAS) was elected to
the first AOV Chair and he pointed out Ryoji Kawabata (GSI) as the Secretary. AOV observations in theframework of the IVS master schedule started at March2015. Takahiro Wakasugi (GSI) and Lucia McCallum(UTAS) assumed as the second Chair and Secretary
since 2017.
AOV is composed of 12 organizations in fivecountries (Figure 2). A total of 19 stations has been
involved in AOV sessions as of the end of 2018.
Observed data are transferred and correlated at the
Tsukuba VLBI Correlator operated by GSI or Shanghai Correlator operated by Shanghai Astronomical
Observatory (SHAO). Scheduling tasks are sharedwith GSI, SHAO, and UTAS (Figure 3). AOV sessions
were carried out six times per year until 2017, andare performed 12 times per year since 2018. Figure 4
shows the summary of AOV sessions planned in 2019.
There are six geodetic sessions and six astrometricsessions this year. All sessions are performed at thedata rate of 1 Gbps. Upgrade of the system at Syowa
station in Antarctica (128 Mbps so far) enalbed us tocarry out such high-rate sampling observations.
AOV face-to-face meetings have been held threetimes so far to exchange information and disucss
various things concerning the AOV. Following theprevious meetings (Hobart, Australia in 2015 andKobe, Japan in 2017), the 3rd AOV meeting took
place from November 9 − 10, 2018 in Canberra hosted
by Geoscience Australia (GA) in conjunction withthe 21st International Laser Ranging Workshop. A
total of 20 people joined the meeting from Australia,
China, Japan, New Zealand, Thailand, Russia, andUSA (Figure 5). The conference is composed of
the group discussion among AOV members, and apresentation-style workshop including two speekers(Michael Pearlman and Toshimichi Otsubo) from SLR
expert as well as speakers from local host organization(Wakasugi and Titov, 2018). The minutes of the group
discussion and all presentation slides are available on
the meeting website (http://auscope.phys.utas.edu.au/
aov/meetings/aov2018/3rdaovgm.html).

Fig. 2: Member organisations of the AOV.

Fig. 3: AOV components.

Fig. 4: AOV sessions in 2019.

3 Conclusions and outlook
The Asia-Oceania VLBI Group for Geodesy and Astrometry (AOV) is an international collaboration in order to foster regional collaboration of VLBI establishedin 2014 as a subgroup of the IVS. AOV has performedinternational geodetic and astrometric VLBI observations regularly. AOV meetings have been held threetimes so far.
Some AOV components have begun their own research towards VGOS. Several intercontinental broad-

118

Fig. 5: Group photo at the 3rd AOV meeting in Canberra.

band experiments have already been performed between Kashima (NICT), Ishioka (GSI), and Hobart(UTAS) stations. In addition, VGOS stations in China
and Thailand will be available in near future. We will
work in close collaboration towards a realization of
VGOS.

References
Kurihara S, Lovell J, Cho J, et al. (2015) Foundation of the
Asia-Oceania VLBI Group for Geodesy and Astrometry. In:
K. D. Baver, D. Behrend, K. L. Armstrong (eds.): IVS 2014
Annual Report, NASA/TP-2015-217532, 20–25
Wakasugi T, Titov O (2018) Geoscience Australia Hosts 3rd
AOV Meeting in Canberra. IVS Newsletter, Issue 52, 6,

T. Wakasugi

Results With the Scheduling Software VieSched++
M. Schartner, J. Böhm

Abstract The Department of Geodesy and Geoinformation at Technische Universität Wien has recently developed a new scheduling software called VieSched++as part of the Vienna VLBI and Satellite Software(VieVS). VieSched++ is written in C++, it features anelaborate backward fill-in mode for minimizing station
idle time and runs multiple versions of the same schedule in a fast batch mode using different optimization
criteria and parameters. Large scale Monte-Carlo simulations with VieVS can then be used for selecting thebest schedule for the purpose of the session within thissample. In particular, the schedules can be optimized
for the given network, source list, observing mode andscientific goal. VieSched++ has already been successfully used for scheduling multiple official IVS sessions.

Keywords Scheduling · VieVS · VieSched++ software

1 Introduction
The first step of every VLBI experiment is the creationof an observing plan, the so-called schedule, which isthen distributed to the participating stations. The schedule makes sure that the observations are synchronized
between the stations and at least two stations observe
the same source simultaneously. Therefore, the schedule determines which sources are observed in which
Matthias Schartner · Johannes Böhm
TU Wien, Department of Geodesy and Geoinformation,
Gußhausstraße 27–29, AT-1040 Vienna, Austria(Correspondence: matthias.schartner@geo.tuwien.ac.at)sequence and also which and how many observations
are later available for the analysis.
While several software packages exist for analyzing geodetic or astrometric VLBI sessions, like
Calc/Solve (Bolotin et al., 2014), the Vienna VLBI
and Satellite Software (VieVS) (Böhm et al., 2018),
OCCAM (Titov et al., 2004), c5++ (Hobiger et al.,2010), Where (Hjelle et al., 2017) or GINS (Bourda
et al., 2007), this is not the case for scheduling. In
the past, almost all geodetic sessions were scheduledwith a software called sked (Vandenberg, 1999)
while astronomic sessions are scheduled using Sched(Walker, 2018). For geodesy and astrometry, the only
notable exception were AUSTRAL sessions (Plank etal., 2017) which were, in the past, scheduled using a
Matlab based scheduler (Sun, 2013) which is part of
VieVS. However, starting in 2018 several observing
programs are now scheduled using a new modern
scheduling software called VieSched++ (Schartner
and Böhm, 2019) which is also part of VieVS. The
following lists shows some of the official International
VLBI Service for Geodesy and Astrometry (IVS)(Nothnagel et al., 2017) schedules, generated with
VieSched++:• AUA (035, 037, 040, 041, 044, 047)
• AUM (001 - 010)
• T2 (129, 130, 131, 132)
• EURR&D (09, 10)• EUR (149)• OHG (171, 118, 119)
• CRF (110)• CRDS (102, 103)
• INT3 (021, 028, 035, 042, 049, 056, 063... 182)
119

120

2 Method
VieSched++ is written in C++ and uses a brute force approach to generate schedules, similar to sked (Gipson,2010). However, all algorithms are newly developed to
be able to generate high-quality schedules. For example, VieSched++ uses a recursive scan selection to minimize station idle time (Schartner and Böhm, 2019a,b).
It provides an automated iterative source selection andgreat care was taken to fine-tune the optimization parameters to implement a good scan selection. Since thecomplexity of optimizing a schedule is very high, VieSched++ comes along with a multi-scheduling feature
which is able to not only generate one single schedule but multiple ones simultaneously. These schedules
can then be used in the VieVS VLBI software directlyfor simulations and based on those simulations the bestschedule can be selected.
More information about the features and algorithms
used in VieSched++ can be found in Schartner andBöhm (2019a).
The schedules further discussed in section 4 arecreated using the multi-scheduling feature. On average, 500 schedules are generated per session varying
the weight factors, as they have the biggest impact on
the scan selection logic, see Schartner et al. (2017) or
Schartner and Böhm (2019a,b). Each of these schedules is simulated 500 times using the VieVS VLBI
software. The simulation includes tropospheric turbulences, clock drifts, and white noise (Pany et al., 2011).
The same simulation parameters are used for all sessions and all stations. The troposphere is simulated using a turbulence simulator with Cn values of 1.8 · 10−7
m−1/3 and a scale height of 2 km (Nilsson et al., 2007).
The clock is simulated using random walk and integrated random walk corresponding to 10−14 at 50 minutes (Herring et al., 1990). Additionally, 30 ps white
noise is added to the observations.

3 Results
In the following subsections, results gained for the
T2, EURR&D and INT3 observing programs are further discussed and compared with previously submitted schedules generated with sked. The schedules generated with VieSched++ are highlighted in blue in Ta-

Schartner and Böhm

ble 1 and Table 2. The fact that the sked schedules are
performing that poorly compared to the VieSched++schedules is not necessarily due to limitations in thesked scheduling software but also due to the fact thatthese schedules were created using bad scheduling parameters. By using different scheduling parameters, thesked solution could be improved as well (John Gipson,
personal communication 2019). However, optimizing
scheduling parameters is not that easy in sked and theseschedules were submitted and observed with this unoptimized schedules.

3.1 T2
The aim of the T2 schedules is to provide accurate
station coordinates for estimating terrestrial reference
frames. These sessions consist of the biggest station
networks of all official IVS sessions with 15 to 22 participating stations. However, the network geometry is
far from optimal. Since most of the stations are in thenorthern hemisphere (Plank et al., 2015) this situationis also reflected in the T2 network geometry. For example, 15 stations are participating in session T2129
but only two of those are in the southern hemisphere,
namely HartRAO and O‘Higgins.
The observations are recorded using a low sampling
rate of 128 Mbit/s which is problematic since some ofthe stations have very low sensitivity with a system
equivalent flux density (SEFD) of more than 10.000.
The suboptimal geometry of the network, together withthe low recording rate makes it especially hard to include O‘Higgins into the schedule. O‘Higgins has very
high SEFD values of 10.000 in X-Band and 18.000 in
S-Band and is located in Antarctica.
Table 1 compares statistics of schedules generated
with sked and VieSched++.
In the previously submitted schedules generated
with sked, the number of observations with O‘Higgins
is always below 100 after 24 hours. One of the goals of
the new schedules is to include O‘Higgins better into
the session. By using VieSched++ it is possible to increase the number of observations with O‘Higgins bya factor of four as can be seen in Table 1.
In general, the number of observations with VieSched++ is about twice the number of observations
with sked, sometimes even three times, while the number of scans roughly stays the same or is even lower.

Results With the Scheduling Software VieSched++

121

Table 1: comparison of statistics between schedules created withsked (top) and VieSched++ (bottom, blue) for T2 sessions#sta #scans #obs %idle %obs #obs Oh
T2123 19617 6773 30.98 50.46
79
T2124 17733 7175 28.10 44.54
22
T2125 17 1064 5528 22.94 53.70
48
T2126 17 1075 6081 24.55 49.66
98
T2127 19627 6304 34.30 45.22
73
T2128 18803 5983 26.24 44.90
97
T2129 15526 12713 8.20 66.90
400
T2130 22626 16730 10.45 69.24
451
T2131 19771 15714 4.33 73.68
267
T2132 18631 10219 6.04 73.37
406
Fig. 1: Sky coverage of stations scheduled with sked (top) and
VieSched++ (bottom).

This means that on average scans with more participating stations are scheduled. Additionally, it is possible
to reduce the idle time of the stations by a factor of
two to three and increase the observing time by almost
50 %.

3.2 EURR&D
Similar to the T2 session, the aim of the EURR&D sessions is to provide high accuracy station coordinates
for terrestrial reference frames. The network consistsof mostly European stations and the observing rate is
512 Mbit/s, which makes it easier to generate a goodschedule.
Table 2 compares statistics of schedules generated
with sked and VieSched++.
Table 2: Comparison of statistics between schedules createdwith sked (top) and VieSched++ (bottom, blue) for EURR&D
sessions#sta #scans #obs %idle %obs
EURD058374 10134 25.00 39.97
EURD06
6538 8061 21.63 30.87
EURD078
344 9437 36.42 29.40
EURD087
361 7215 25.78 33.08
EURD09 8665 11565 5.78 39.03
EURD10 8
669 13480 3.08 42.70

Compared to the results from T2 listed in Table 1
the improvement regarding scheduling statistics seems
lower based on the statistical values. However, VieSched++ is able to generate schedules with a higher
number of observations but this time the number ofscans also increases. The main difference between thesked schedules and the VieSched++ schedules is thesky coverage of the stations as shown in Figure 1. Since
sked only schedules scans with the full network it focuses mainly on one small part of the sky. This resultsin low slew times and thus many observations but also
in a very poor sky coverage as shown in Figure 1 for
EURD07. In contrast VieSched++ decides to split the
network more often resulting in a way better sky coverage as shown in Figure 1 for EURD09. A good sky coverage helps to estimate tropospheric time delays which
are one of the major error sources in geodetic VLBI
(Schuh and Böhm, 2013). Especially observations at
different elevations are necessary to distinguish tropospheric delays, clocks and station heights which arehighly correlated (Nothnagel et al., 2002).
Compared to the sked solutions it is possible to reduce the idle time by a factor of four to five as shownin Table 1. The time gained is used mostly for slewing
purposes to achieve better sky coverage.

3.3 INT3
The purpose of the INT3 sessions is to provide dUT1
values. The network consist of four to five stations,the observing rate is 1024 Mbit/s and the session duration is only one hour. Since the complexity of intensive
schedules is relatively simple due to the low number ofstations and short session duration, scheduling of intensive sessions is rather easy compared to global 24hour sessions. Therefore, it was not expected to gainsignificant improvement when changing from sked to
VieSched++. However, Figure 2 shows that even for

122

Schartner and Böhm

Fig. 2: Number of observations in INT3 sessions color-coded by number of participating stations.

intensive sessions the number of observations can be
improved.
Figure 3 shows the dUT1 formal error gained from
intensive sessions as they are listed in the analysis reports. The values are color-coded by the number of participating stations, the analysis center which delivered
the analysis report and by the observing rate. Figure 4
shows the same values, but this time only the INT3 sessions are colored. Starting with 21st of January 2019,
VieSched++ is used to generate these schedules.
It can be seen that the INT3 sessions provide themost accurate dUT1 estimates, due to the higher number of stations and the higher observing rate. While
Figure 2 shows the number of scheduled stations, Figure 3 and Figure 4 show the number of stations whichwere actually observing the session, since it can happen that one station drops out.

Fig. 3: dUT1 formal errors from intensive sessions listed inFig. 4: dUT1 formal errors from INT3 sessions listed in analysis

analysis reports, color-coded by number of stations, analysis
center and sampling rate.

reports, color-coded by number of stations, analysis center andsampling rate.

Figure 4 shows, that by changing the schedulingsoftware to VieSched++ the formal errors of the dUT1
values is improved to solutions from the previous
half year. At the beginning of 2018, the accuracy was
roughly at the same level, while after April 2018 theresults got significantly worse. It is unclear why thishappened, however, it corresponds with a time period
where the number of observations was also very low
as seen in Figure 2.

Results With the Scheduling Software VieSched++

4 Conclusions and outlook
VieSched++ is a new, modern VLBI scheduling software written in C++. It uses many new features andalgorithms to generate high-quality schedules. While
generating optimized schedules for VLBI experiments
should be the norm, unfortunately, this is not the case.
This work shows, that it is possible to achieve twice
the number of observations compared to previously uploaded results. Based on the newly created optimizedschedules, improvements can also be expected during
analysis for these sessions. Unfortunately, so far this
could only be verified for INT3 sessions since mostother sessions are not yet correlated and no VgosDB
database are available for analysis at the moment.
While VieSched++ is already stable andfreely available through our GitHub pagehttps://github.com/TUW-VieVS, development continues to improve the quality of the generated schedules
even further. Additionally, a YouTube channel called“VieVS” is available, where the usage of VieSched++
is explained.

ReferencesBöhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry. PASP,
130, 044503, doi:10.1088/1538-3873/aaa22b
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Analysis Software νSolve: Development Progress and Plans
for the Future. In: D. Behrend, K. D. Baver, K. L. Armstrong (eds.): IVS 2014 General Meeting Proceedings, Science Press (Beijing), 253–257
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the GINS software for multi-technique combination at theobservation level. Proceedings of the Annual meeting of theFrench Society of Astronomy and Astrophysics, 82
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of very long baseline interferometry data. J Geophys Res,95, 12561–12581, doi:10.1029/JB095iB08p12561
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Software for Geodetic Analysis. EGU General Assembly
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Nilsson T, Haas R, Elgered G (2007) Simulations of atmospheric path delays using turbulence models. Proc. 18th
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Meeting Proceedings, NASA/CP-2002-210002, 260–264
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VLBI Service for Geodesy and Astrometry. J Geod, 91,
711–721 doi:10.1007/s00190-016-0950-5
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errors on the repeatability of VLBI positions. J Geod, 85,
39–50, doi:10.1007/s00190-010-0415-1
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for geodetic VLBI in the southern hemisphere. ASR, 85,
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Schartner M, Böhm J, Mayer D, et al. (2017) Recent Developments in Scheduling with VieVS. In: R. Haas, G. Elgered(eds.): Proc. 23rd EVGA Working Meeting, 113–116
Schartner M, Böehm J (2019a) VieSched++: A New VLBI
Scheduling Software for Geodesy and Astrometry. PASP,
131, 084501, doi:10.1088/1538-3873/ab1820.
Schartner M, Böehm J (2019b) VieSched++: A new Scheduling Tool in VieVS. In: K. L. Armstrong, K. D. Baver,D. Behrend (eds.): IVS 2018 General Meeting Proceedings,
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Schuh H, Böehm J (2013) Very Long Baseline Interferometryfor Geodesy and Astrometry. Berlin, Heidelberg: Springer,
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Walker R C (2018) The SCHED user manual.

INT9 - ∆UT1 Determination Between the Geodetic
Observatories AGGO and Wettzell
C. Plötz, T. Schüler, H. Hase, L. La Porta, M. Schartner, J. Böhm, S. Bernhart, C. Brunini, F. Salguero,
J. Vera, A. Müskens, G. Kronschnabl, W. Schwarz, A. Phogat, A. Neidhardt, M. Brandl

Abstract The AGGO radio telescope, located at
La Plata in Argentina, comprises together with theradio telescopes in Wettzell, Germany a baseline
configuration spanning a longitude difference of 71°.
Therefore, starting in the middle of 2018, tests were
initiated to prove the usability for ∆UT1 determination between the traditional S/X VLBI systems at
AGGO and Wettzell. The 6 m AGGO radio telescope
was scheduled in combination with the 20 m radio
telescope Wettzell (RTW) and the 13.2 m Wettzell
Christian Plötz · Torben Schüler · Gerhard Kronschnabl · Walter
Schwarz · A. Phogat
Geodätisches Observatorium Wettzell, Bundesamt für Kartographie und Geodäsie (BKG), Sackenrieder Str. 25, DE-93444 Bad
Kötzting, Germany
Hayo Hase
Argentinean German Geodetic Observatory, Bundesamt für Kartographie und Geodäsie (BKG), Sackenrieder Str. 25, DE-93444
Bad Kötzting, Germany
Claudio Brunini · F. Salguero · J. Vera
Argentinean German Geodetic Observatory, Conicet, Camino
Gral. Belgrano Km 40 - Berazategui, Provincia de Buenos Aires,
Argentina
Alexander Neidhardt · M. Brandl
Forschungseinrichtung Satellitengeodäsie (FESG), Technische
Universität München, Sackenrieder Str. 25, DE-93444 Bad
Kötzting, Germany
Matthias Schartner · Johannes Böhm
TU Wien, Department of Geodesy and Geoinformation,
Gußhausstraße 27–29, AT-1040 Vienna, Austria
Arno Müskens
Institute of Geodesy and Geoinformation, University of Bonn,
Nußallee 17, DE-53115 Bonn, Germany
Laura La Porta · Simone Bernhart
Reichert GmbH/BKG, Hittorfstr. 26, DE-53129 Bonn, Germany(Correspondence: ploetz@fs.wettzell.de)

North (WETTZ13N) in weekly VLBI tests for ∆UT1
determination, named INT9. The scheduling of INT9
sessions was done with sked and the time duration
was set to be two hours each. The sessions were conducted mostly on Thursdays, just before the normal
INT-1 Intensive session takes place. The recording
mode needed to be evaluated step by step to increase
gradually from a standard 256 Mbit/s recording modeto 1 Gbit/s. The latter mode yields a higher amountof scans in a given time period. The goal is to exploit
the highest ∆UT1 determination accuracy between
AGGO and Wettzell as possible. We will report our
initial experiences with the VLBI operation at bothobservatories and compare first results between official∆UT1 measurements and the INT9 derived values aswell as a potential future outlook of this INT9 VLBI
application.

Keywords Intensive · ∆UT1 · Geodetic Observatory
Wettzell · AGGO

1 Introduction
The Argentinean German Geodetic Observatory(AGGO) was successfully re-initiated after the transport from Chile to Argentina. Due to the extended idle
period, several components of the VLBI system were
defect or showed malfunctions.
In particular, the analog baseband converters andthe up-converter of the analog backend had failuresand needed to be repaired. After this maintenance, the
VLBI system at AGGO became operational in spring2018. The VLBI system needed to be tested carefully124

INT9 - ∆UT1 Determinationand its stability had to be evaluated, before taking partagain in the normally scheduled VLBI sessions within
the International VLBI Service (IVS) (Nothnagel
et al., 2017). This was done first with test sessions
coordinated between the Bundesamt für Kartographie
und Geodäsie (BKG) radio telescopes of the Geodetic
Observatory Wettzell and AGGO. When the first
fringes were successfully found, the demand cameup to evaluate geodetic VLBI applications. A ∆UT1
determination is a favorable geodetic application, due
to the longitude difference of 71° between AGGO
and Wettzell. Therefore, a demonstration program
including a series, consisting of test sessions was
initiated to prove that this baseline configuration is
sufficient for the ∆UT1 determination.

125

Fig. 2: The 20 m radio telescope Wettzell (RTW).

The 20 meter radio telescope Wettzell (RTW or
Wz) of the geodetic observatory Wettzell constitutes astable reference station within the VLBI community
since 1983. Especially, the ∆UT1 Intensive measurement INT-1 with a one hour session between the RTW
and the 20 meter radio telescope of Kokee Park isnormally observed every week from Monday until
Friday. Thus, a comparison of the ∆UT1 performanceof the Wettzell to AGGO baseline in relation to thefrequently observed baseline Wettzell to Kokee Park
would be of high interest. Another aspect is thatthe most VLBI stations are located on the northernhemisphere, including VLBI stations that are involvedin frequent Intensive ∆UT1 VLBI measurements,
whereas AGGO is located on the southern hemisphere.
Additionally, the difference in latitude of 84° mightprovide information about an estimate of the polar

motion. Though, the pole position was held fixed inthose initial investigations.

Fig. 1: The 6 m radio telescope AGGO.

Fig. 3: The 13.2 m twin radio telescopes Wettzell.

The challenges to overcome were to establish thecomplete processing chain, i.e. scheduling the Intensive session, correlating with the DiFX software correlator (Deller et al., 2007) and obtaining results fromanalysis. The main limitation is the rather high system equivalent flux density (SEFD) of the AGGO radio
telescope. Therefore, with the same observing mode
(256 Mbit/s) as for an INT-1 Intensive observation, arather long observation time on a radio source is necessary to reach a minimum signal to noise ratio (SNR)
goal of 20 in X-band and 15 in S-band. The tests werethen focused to test the 1 Gbit/s mode, which is also
feasible with the old analog backend of AGGO. This
1 Gbit/s mode is used successfully with the weekly
INT-3 Intensive observations.

126

2 Method
Several issues needed to be solved in order to reachIntensive observation capability. The scheduling wasdone initially with the scheduling program sked (Gipson, 2010) and later on with VieSched++ (Schartner andBöhm, 2019). As a first approach, the formerly proven
VLBI mode with 256 Mbit/s and one-bit sampling waschosen. This is a standard mode in R1 sessions and was
frequently used before with IVS-R1 sessions at AGGO.
Hence, the first test observation resulted in immediate
fringes and analysis results. The SEFD of the 20 meter RTW is 750 Jy in X-band and 1000 Jy in S-band.
In contrast, the values of AGGO are 10000 Jy in Xband and 15000 Jy in S-band. The only way to achieve
more scans per observation time is to increase the total
data rate to yield a reasonable number of scans within
two hours of Intensive observation time, with the given
antenna characteristics. Thus, the use of the 1 Gbit/s
mode was clearly the preferred observation mode, because this one enables more scans and leads to better
analysis results as the 256 Mbit/s total data rate mode.
However, it was quite tricky to set up the backend properly with the VLBA4 analog backend of AGGO during
these tests. In particular the trackform layout for the
DiFX software correlator, which has to be set up in thesession vex file, turned out to be more complicated than
expected. The raw data was correlated at the VLBI cor-Plötz et al.

relator in Bonn first and then some sessions were correlated at Wettzell. The analysis of the INT9 sessions
was done with VieVS (Böhm et al., 2018) at the TU Vienna.

Table 1: Characteristic antenna parameters.

RTW TTW1 AGGO
(Wz) (Wn) (Ag)antenna diameter (m)20 13.2
6
S-SEFD (Jy)1150 1050 15000
X-SEFD (Jy)750 1400 20000
Az-speed (° s−1 )4
126
El-speed (° s−1 )1.5
62

The twin radio telescope TTW1 (WETTZ13N orWn) is equipped with a S/X/Ka-band receiving system and scheduled regularly in the IVS observation
program. Depending on the availability of the respective telescopes, this Wettzell radio telescope was alsoscheduled alone or even together with the 20 m radio telescope in conjunction with AGGO. This leads
to three different baseline configurations.
• Ag – Wz• Ag – Wn• Ag – Wn – Wz
In general, the session scheduled with all three radio telescopes is expected to give the best accuracy of
the UT1 formal error. Most of the observations werescheduled on Thursdays between 16 and 18 UT before
the regular INT-1 session between Wettzell to Kokee
Park takes place.

3 Results

Fig. 4: Baseline configuration of AGGO and Wettzell. The dis-

tance between Wz and Ag appears as surface distance.

The first analysis results of the session wb207q, observed with the 256 Mbit/s mode, showed an UT1 formal error of 105 µs. The number of scans is very low,
only 25 scans in two hours and no further improvements like consolidated coordinates of AGGO were applied.
The next milestone could be achieved when the
1 Gbit/s observation mode worked correctly. The session wb213q consisted of 35 scans within two hoursof observation. This caused the UT1 formal error todecrease by almost 50 % to 56 µs. Consequently, theINT9 - ∆UT1 Determination

127

Fig. 5: ∆UT1 with respect to C04.

triple configuration with both radio telescopes involvedat Wettzell and AGGO lowered the formal error of UT1
to 48 µs again.
Figure 5 depicts the UT1 estimates as well as theirformal uncertainties in contrast to the IERS-C04 timeseries. For comparison, the INT-1 estimates (XU) andtheir formal uncertainties are displayed as well. It canbe seen that the estimates of the 1 Gbit/s agree quite
well with the INT-1 results. The formal uncertainties
tend to be a bit higher than their INT-1 counterparts. It
is expected that the accuracy increases as soon as thestation coordinates of the relatively new AGGO station are known more precisely. Additionally, further
improvement is expected as soon as the scheduling isfine-tuned.
Simulations of this triple configuration yield a UT1formal error of about 30 µs. The simulations were madeusing VieVS according to Pany et al. (2011) and include tropospheric time delays, clock drifts and white
noise. The troposphere was simulated with Cn valuesof 1.8 · 10−7 m−1/3 , a scale height of 2 km and a constant wind velocity of 8 m/s towards east (Nilsson etal., 2007). The clock was simulated as the sum of arandom walk and an integrated random walk with an
Allan standard deviation (ASD) of 1 × 10−14 seconds

after 50 minutes (Herring et al., 1990). Finally, 30 psof white noise was added to the observations.
Unfortunately, it turned out that the schedules of theobserved sessions were not fully optimized for the sessions. Figure 6 compares the simulated formal errors
between different scheduling approaches. By using VieSched++, optimized schedules are generated and compared with the observed schedules based on simulations. It can be seen that it is possible to increase both,the number of observations per session as well as the
expected formal uncertainties of the UT1 estimate.

4 Conclusions and outlook
The initial performance of the INT9 test sessions between AGGO and both Wettzell radio telescopes is encouraging. If everything is settled a formal UT1 error of about 30 µs appears to be feasible. The upgradeof the analog VLBA4 backend system with a DBBC2
is planned by the end of 2019 or the beginning of
2020. This might improve the system performance andstability of AGGO. Further improvements can be expected by optimizing the scheduling and selecting thesources more carefully as done in Gipson and Baver128

Plötz et al.

Fig. 6: INT9 comparison between simulation and measurement. The indicated UT1 formal error was determined by simulation. The
UT1 error shows the results gained by the observations.

(2015). Then a test of even 2 Gbit/s total data rate
might be an option to get more scans per observation.
Further careful evaluation of important parameters likesource selection, correct application of the radio telescope specific peculiar time offsets, radio frequency interference (RFI) avoidance zones, consolidated coordinates of AGGO could improve the results of ∆UT1.
A routine setup of a triple radio telescope configuration, consisting of RTW, TTW1 and AGGO might yield
the best formal errors. Regularisation of the INT9 campaign including a rapid correlation and subsequent data
analysis is foreseen in 2019 and 2020. Finally, AGGO
demonstrated its potential to a self-contained estimation of ∆UT1.

ReferencesBöhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry, PASP,
130(986), 044503, doi:10.1088/1538-3873/aaa22b
Deller A, Tingay S, Bailes M, et al. (2007) DiFX: A software
correlator for very long baseline interferometry using multi-

processor computing environments. (Swinburne U., Ctr. Astrophys. Supercomput.). Feb 2007. 41 pp. PASP 119, 318,
doi:10.1086/513572
Gipson J (2010) An Introduction to Sked. In: D. Behrend,
K. D. Baver (eds.): IVS 2010 General Meeting Proceedings,
NASA/CP-2010-215864, 77–84
Gipson J, Baver K (2015) Improvement of the IVS-INT01
sessions by source selection: development and evaluationof the maximal source strategy. J Geod, 90(3), 287–303,
doi:10.1007/s00190-015-0873-6
Herring T, Davis J, Shapiro I (1990) Geodesy by radio interferometry: The application of Kalman Filtering to the analysis
of very long baseline interferometry data. J Geophys Res,95, 12561–12581, doi:10.1029/JB095iB08p12561
Nilsson T, Haas R, Elgered G (2007) Simulations of atmospheric path delays using turbulence models. Proc. 18th
EVGA Working Meeting, 175–180
Nothnagel A, Artz T, Behrend D, et al. (2017) International
VLBI Service for Geodesy and Astrometry. J Geod, 91,
711–721, doi:10.1007/s00190-016-0950-5
Pany A, Böhm J, MacMillan D, et al. (2011) Monte Carlo simulations of the impact of troposphere, clock and measurement
errors on the repeatability of VLBI positions. J Geod, 85,
39–50, doi:10.1007/s00190-010-0415-1
Schartner M, Böhm J (2019) VieSched++: A New VLBI
Scheduling Software for Geodesy and Astrometry. PASP,
131, 1002, doi:10.1088/1538-3873/ab1820

LCONT18 - The Local Continuous Measurement Campaign at
the Geodetic Observatory Wettzell of 2018
T. Schüler, C. Plötz, G. Kronschnabl, W. Schwarz, A. Neidhardt, M. Brandl, L. La Porta, S. Bernhart

Abstract LCONT18 was the local continuous measurement campaign of the year 2018 to derive local
ties, i.e. relative radio telescope positions, at the Observatory. The baseline adjustment was performed using X-band group delay data at the traditional center
frequency of 8.6 GHz. Ionospheric delays cancel out
due to high spatial correlation over these baselines as
short as 123 m and less. Data were collected over two
weeks. Preliminary analysis results of an initial subset
of data are presented in this paper. Compared to otherlocal experiments conducted between 2015 and 2017,
the LCONT18 data set suffers from X-band radio interference. Though S-band interference is common, problems in X-band have not yet registered so far. However,millimetre repeatability can still be reached.

Keywords Local radio telescope positioning · Local
ties · Short baseline interferometry · Geodetic Observatory Wettzell · LCONT

Torben Schüler · Christian Plötz · Gerhard Kronschnabl · Walter
Schwarz
Geodetic Observatory Wettzell, Federal Agency for Cartography
and Geodesy, Sackenrieder Str. 25, DE-93444 Bad Kötzting
Torben Schüler also
University of the Federal Armed Forces Munich, Faculty of
Aerospace Engineering, DE-85577 Neubiberg
Alexander Neidhardt · Martin Brandl
Geodetic Observatory Wettzell, Technical University Munich,
Sackenrieder Str. 25, DE-93444 Bad Kötzting
Laura La Porta · Simone Bernhart
Bonn Correlator, Reichert GmbH
(Correspondence: schueler@fs.wettzell.de)

1 Introduction
The Wettzell radio telescope triple is a local network of
VLBI telescopes comprising two VGOS-capable systems with an antenna aperture of 13.2 m and one traditional system with a diameter of 20 m. Each of thesetelescopes has its individual receiving system at the
moment: Whilst Wz (RTW, the 20 m telescope) features a legacy S/X-receiver, Wn (”Wettzell North” TWIN1) can be equipped with either a tri-band receiver (S/X/Ka) or a broadband feed (not used in thiscampaign), and Ws (”Wettzell South” - TWIN2) isequipped with a broadband receiver (”Elevenfeed”).
LCONT18 was a local intensive measurement
campaign between Dec, 3rd and Dec, 14th 2018. For
the first time, the complete network observed bothsynchronously and continuously for a duration of
two weeks (twice 5 working days in sequence). It
is named in analogy to the well-known international
CONT-campaigns organized by the IVS. Data werecollected in a standard 256 Mbit/s recording modewith a duration of up to 24 hours from Monday till
Friday. The individual baselines WzWn as well as
WnWs had been tested before minimizing the risk offailure.
LCONT18 is the most exhaustive local campaign
planned so far at Wettzell. This is important, because
the individual baselines observed up to now are not sufficient to assess all essential/substantial questions related to the relative radio telescope positioning over local baselines. In summary, the purpose of this measurement campaign is as follows:
1. We want to investigate the day-to-day repeatabilityof the local telescope coordinates (local baselines)
in detail. The period at the beginning of December
129

130

Schüler et al.

Fig. 1: Local radio telescope baselines are used as tight relative

coordinate constraints to obtain rigid relative telescope positions
when serving as an array to network observations requiring highcoordinate precision.

Fig. 2: Receiver setup at the three local telescopes: The tradi-tional S-/X-setup of Wz (20 m, RTW) is raised as a standard forthe network observations. X-band data at the identical center frequency of 8.6 GHz are recorded at both Wn and Ws.

2018 is a suitable time slot for this, because a local
terrestrial survey was conducted right in advance.
Automatic local GPS positioning is operational
since 2014 at Wettzell yielding sub-millimetre repeatability between (weekly) solutions. The accuracy potential of VLBI will be compared to that ofGNSS.
2. The best compromise between observation duration and baseline accuracy will be investigatedhaving full data sets of up to 24 hours each day.
3. Observing with three telescopes allows us assessing possible loop closure errors. Such errors canstem from residual source structure uncertainties,
but more likely from remaining clock and othersystem-related errors. Hence, LCONT18 will provide a better insight into the systems compared to
all local activities carried out so far.

Apart from the experimentation purposes outlined
before, it should be mentioned that precise local ties areof high importance. The precise relative positions will
be used as tight constraints in global adjustments. Thisis particularly important for short Intensive-like (INT)
sessions where the three Wettzell telescopes can serve
three individual partner telescopes - see Fig. 1. Coordinates are usually held fixed in Intensive sessions.
We will report about our operational experiences
gained during this campaign, and will portray first results for the network adjustment.

2 Method
Data were sampled using a rate of 256 Mbit/s, similarly
to previous local experiments and current IVS Rapid
sessions.
The three telescopes at Wettzell feature different
receiving systems as indicated in Fig. 2. We preferred to run the network in a conventional mode
during LCONT18 mainly focusing on group delay
observations at the traditional 8.6 GHz X-band center
frequency. A future LCONT campaign may exploit theadditional capabilities of the two TWIN telescopes,
e.g. it is possible to sample two X-band windows withWn (TWIN1) and Ws (TWIN2).
The signals measured by Wz (RTW 20 m) as wellas Wn (TWIN1) are received in circular polarisation(RHCP), whereas Ws (TWIN2) received the signals indual linear polarisation. As a consequence, the correlation process involving Ws will provide two geodetic
input files with group delays derived from vertical aswell as horizontal polarisation raw data.
The session planning was supported by the coordination software LEVIKA IVS SU (Schüler et al.,2018), scheduling was done using sked.
The group delay observations were adjusted using in-house software LEVIKA SBA (Short Baseline
Analysis). We performed data pre-screening and derived the number of clock error estimation intervals

LCONT18 at Geodetic Observatory Wettzell

131

Fig. 3: Local VLBI telescope ties from precision terrestrial surveying; Earth-centered Earth-fixed coordinate system. These ties serve

as reference values for LCONT18.

with help of a linear filter. This means that a flexible number of estimation intervals is defined individually rather than setting the estimation interval to a fixedvalue (e.g. one hour).
The local relative positions of the telescopes are by
far more precise than long baseline coordinate results
due to the virtual identity of the atmospheric delays
within the distances of less than 200 m at Wettzell.
However, the height difference between the old andthe two new telescopes has to be taken into consideration in tropospheric delay modelling since it means achange in pressure and thus a millimetre-range change
in zenith hydrostatic delay. In contrast, the two TWINtelescopes are exactly located at the same height level.
Tropospheric delay compensation was enabled by default (Schüler, 2014). However, we did not estimate
any additional tropospheric delay nuisance parameter,
because these parameters turned out to be statisticallyinsignificant.

3 Results
Fig. 4 shows the observation statistics of the selected
LCONT18 sessions presented in this contribution.
Column n is depicting the number of group delay

observations (scans) actually used in the adjustment
process. Though the two TWIN-telescopes exhibit
VGOS slew speeds (12 ◦ /s in azimuth and 4 ◦ /s inelevation direction), the maximum number of observations achievable in this network is limited by Wz(RTW, 20 m). That telescope is slewing at a speed ofmax. 4 ◦ /s (azimuth) and 1.5 ◦ /s (elevation) limiting
the number of scans to approximately 1,000 within
24 hours. Interruptions of LCONT18 by INT-sessions(Intensives, UT1-determination) were permitted.
Consequently, the total number of observations is
expected to be a bit smaller here.
However, the actually achieved observation statistics are considerably smaller, and particularly low on
Dec, 12th . A large amount of X-band data was rejected resulting in a major loss of geodetic observations. Fig. 6 portrays this situation graphically for theselected day: Red vertical lines indicate group delay
observations that had been deleted as a result of thedata pre-screening procedure. A major loss of data occurs between 9 h and 13 h UT. The source of radiofrequency interference, either internal or external, isstill unclear. Normally, X-band data are less affectedby contaminating RFI compared to S-band data (usually omitted in local analysis). This phenomenon was
not observed during previous local sessions (Schüler
et al., 2015; Halsig et al., 2018).

132

Fig. 4: Preliminary LCONT18 session analysis: Both horizon-tally and vertically polarised signals received by Ws can be correlated with the data of the other telescopes. ”WETTZ13N” isWn (TWIN1), ”WETTZ13S” is Ws (TWIN2) and WETTZELL
is Ws (RTW). n∆T indicates the number of clock error compensation intervals in the parameter estimation process. It is zero for
the TWIN telescope baseline since these telescopes have a common clock. n is the number of observations (scan, group delays)
after data pre-screening and outlier rejection. s0 is the standard
deviation of unit weight à posteriori representing the precision ofa single group delay in X-band.

Fig. 5: Preliminary LCONT18 session analysis: ∆S indicates the

3D spatial deviation of the LCONT18 baseline adjustment fromthe local terrestrial surveying results

The clock error estimation intervals vary considerably between 5 and 17. A small number indicates aclock drift behaviour that appears to be close to a linear
drift. Surprisingly, the baseline Wn-Wz features 10 and
12 clock intervals on Dec, 3rd , whereas the number isjust 5 for the baseline Ws-Wz, although both Wn and
Ws are connected to the same hydrogen maser. Thissuggests that other impacting error sources are dominant rather than the maser itself. One possible sourceof instability can be the cable delay unit (not yet activated at the TWIN telescopes during LCONT18) or,
theoretically, the digital back-ends.

Schüler et al.

The standard deviation of unit weight à posteriori
is in the range of less than 5 mm, i.e. usually around
10 ps or less. This is slightly higher than previous sessions, but can be explained by the higher level of radio
interference.
The spatial deviations from the precision surveying results are randomly distributed for the baselines
WnWz as well as WsWz and in the range of a couple of millimetres. Once again, this exceeds previous
experiences a bit (i.e. around one millimetre with atendency to the sub-millimetre domain), see Phogat etal. (2018). Note that baseline WnWs between the two
TWIN-telescopes seems to be systematically biased,though the magnitude equals the results obtained forthe other baseline. This requires further attention.

4 Conclusions and outlook
LCONT18 was carried out at the end of year 2018 over
two working weeks. A limited first set of data and results is presented in this paper. The results reveal that
there is still plenty of work to do.
Both data quality and results are slightly inferior
compared to previous local experiments (that had usually been limited to baseline WnWz), though the data
are still usable. A considerably high level of radiofrequency interference was observed during some of
the LCONT18 days yielding a data loss of 10 % to
30 %. The baseline accuracy is degraded by a factorof two or even three compared to previous experiments
and is in the range of one to three millimetres.
Regarding our future work, we firstly will analyse
the complete data set and try to tackle down the problems revealed. One important aspect is also to determine the best compromise between session duration
and baseline accuracy, since we assume that less than
24 hours of observation are sufficient under real local
conditions. Moreover, the investigation of the usage ofphase rather than group delays can be of value for the
future, though it will currently not be much effective incase RFI limits the accuracy. That, however, is a newphenomenon observed for the first time at Wettzell, andhas to be traced back and mitigated accordingly.
Subsequently, the local sessions will be distributed
equally over the year to continuously obtain local relative positions of the telescopes in order to provide
tight baseline constraints for all experiments carried

LCONT18 at Geodetic Observatory Wettzell

133

Fig. 6: Fails.

out at Wettzell including more than one local telescope.
These local routine sessions are foreseen to take placeeach two months in order to capture possible annual
deviations (”annual wave”).
Acknowledgements We gratefully acknowledge the support ofthe Bonn Correlator. This work was carried out in the framework of the project ”GeoMetre” as part of the EMPIR initiative. 18SIB01 GeoMetre is receiving funding from the EMPIR
programme co-financed by the Participating States and from theEuropean Union’s Horizon 2020 research and innovation programme.

References
Halsig S, Bertarini A, Haas R, et al. (2018) Atmospheric refraction and system stability investigations in short-baseline

VLBI observations. J Geod, doi:10.1007/s00190-018-11845
Phogat A, Kronschnabl G, Plötz C, et al. (2018) Short Baseline
Observations at Geodetic Observatory Wettzell. Data, 3, 64,
doi:10.3390/data3040064
Schüler T (2014) The TropGrid2 standard tropospheric correction model. GPS Solut, 18:123, doi:10.1007/s10291-0130316-x
Schüler T, Kronschnabl G, Plötz C, et al. (2015) Initial Results
Obtained with the First TWIN VLBI Radio Telescope at theGeodetic Observatory Wettzell. Sensors , 15, 18767-18800,
doi:10.3390/s150818767
Schüler T, Plötz C, Phogat A (2018) BKG CVC - The Central VLBI Observation Coordination Office of the Federal
Agency for Cartography and Geodesy at the Geodetic Observatory Wettzell. In: K. L. Armstrong, K. D. Baver,D. Behrend (eds.): IVS 2018 General Meeting Proceedings,
NASA/CP-2019-219039, 135–139

Preliminary Work on Promoting Radar Astronomical Study
J. Sun, J. Ping, S. Han, F. Shu, L. Ma, W Chen, L. Cui

Abstract Radar astronomical observations provide information on surface characteristics, orbits, and rotations for a wide variety of solar system objects. Basedon a complex of radio telescopes of the Chinese VLBI
network (CVN), in cooperation with the domestic radartransmitters, we present the current radar astronomical observations to the Moon. The spectrum of thereflected radio signals was obtained and the Doppler
frequency shift in bistatic radar mode was measured.
And the powers ratio of the reflected signals with leftand right-hand circular polarizations was determined,
which allowed to stuy the near-surface wavelengthscale roughness of the Moon. The future radar astronomical developments, taking into consideration thepossible international joint observations, are also introduced in the paper.

Jing Sun · Jinsong Ping
National Astronomical Observatory, 20A Datun Road, Beijing
100101, China
Songtao Han
Beijing Aerospace Control Center, 26 Beiqing Road, Beijing
100094, China
Fengchun Shu
Shanghai Astronomical Observatory, 80 Nandan Road, Shanghai
200030, China
Langming Ma
National Time Service Center, 3 Shuyuandong Road, Xian
710600, China
Wen Chen
Yunnan Observatory, P.0.Box110, Kunming 650011, China
Lang CuiXinjiang Astronomical Observatory, 150 Science 1-Street,
Urumqi 830011, China(Correspondence: sunjing@bao.ac.cn)

Keywords Radar VLBI · Moon

1 Introduction
Radar astronomy is one of the most effective techniques for determining the physical properties and orbital elements of the planets and small bodies in thesolar system. The size, shape, spin period, and surface
properties can be obtained using radar observations.
Progressive updates of the NASA Goldstone and NSF
Arecibo systems, primarily by moving to higher frequencies and more powerful transmitters, have madethese two radar systems the dominant instruments for
current radar studies of the solar system (Ostro et al.,2007).
Based on the project of the Low Frequency VLBI
Network (LFVN), the VLBI radar (VLBR) for theinvestigations of the solar system bodies have beendeveloped. LFVN arranges VLBR experiments since1999 with the help of the C-band transmitter of Evpatoria RT-70 and X-band transmitter of Goldstone RT70. The VLBR combines the radar sounding of space
objects with a powerful transmitter and the receivingof radar echoes by an array of radio telescopes in
VLBI mode. The VLBR supplements the traditional
radar methods with the interferometric reception ofa ground-based transmitter’s signal reflected from theobject (Nechaeva et al., 2015, 2013). VLBR allows tomeasure the variations of proper rotation of the Earthgroup planets and determine the trajectories of planets and asteroids in the Radio Reference Frame (Ipatov et al., 2016). VLBR has successfully been tested
in a large series of international experiments: study ofshort-periodic variation of proper rotation for the Earth134

Promoting Radar Astronomy

group planets, improving the orbits of asteroids crossing the Earth orbit, measuring the space debris population at geo-stationary and high-elliptic orbits (Molotov
et al., 2008; Tuccari et al., 2006).
There are several fully steerable dishes equippedwith powerful X band transmitter in China, that areused for the deep spacecraft communications. The
close collaboration of radar transmitters with the
Chinese VLBI network (CVN) gives the opportunity
to apply the VLBI technique for receiving and analysis
of echo signals. The first successful radar detectionof the Moon was carried out on Jul. 2, 2017. Since
2017 radar observations are regularly organized at the
National Astronomical Observatory of the Chinese
Academy of Sciences (NAOC) in cooperation withthe domestic radar instruments to transmit and theradio telescopes of the CVN to receive the echoes.
Primary goal is developing and validation of the radar
astronomical method to obtain the information on
trajectory parameters, attitude motion, and shape for
known objects. The efforts of six sessions during
2017-2019 were concentrated on the observations to
the Moon.

2 Experiments
A collaboration program is in development with thedomestic radar team was initiated in 2017, and six experiments have been carried out for radar astronomical research of the Moon. The radar transmitter and acomplex of radio telescopes spaced by hundreds andthousands of kilometers were the basis of the experimental facilities. Preparing for pointing of all antennas
was done by the ChangE-3 lander coordinates. The domestic radar antenna illuminated the Moon with continuous wave (CW) signal at a frequency of X band in
left-hand circular polarization. The carrier frequency
was not changed over time and the transmitter power
reached 8 kW. The signal reflected from the Moon wasreceived in the VLBI mode with the radio telescopes of
the CVN simultaneously in left- and right-hand circularpolarizations, i.e. in the same (SC) and opposite (OC)circular polarizations as that of the transmitted wave.
Data recording was carried out in the frequency bandof 2 MHz. The echo signal was quantized and written
in digital form on the Mark5B modules.

135

The echo signals reflected from the Moon wereconfidently detected by each antenna in all the sessions,which provided reliable data at all stages of processing.
After the radar sessions, the echo rawdata from each receiving antenna were transmitted to NAOC for further
data processing.

3 Preliminary results
A spectral analysis of the received signal at each
receiving point was done for further calculation of
frequencies. The spectral analysis of the obtained
information was to measure the frequency difference
between the emitted and the received signals. The
difference, namely Doppler frequency shift, is conditional on the radial velocity of the object on the track”transmitter-Moon-receiver”. The Doppler shift wasdetermined using the peaks of the frequency spectra.
Using the fast Fourier transform, the frequency of
Doppler shift is measured in one-second intervals witha frequency resolution of 1 Hz from our measurements.
The spectra of the signals reflected from the Moon
were received with the Kunming RT-40 and Sanya RT13 simultaneously over the entire interval of our observations, as presented in Fig. 1 and Fig. 2, respectively. Solid and dashed lines denote echo power in the
OC and SC polarizations. The vertical axis shows theamplitude of the received signal in relative units, horizontal axes display frequency in Hertz. Echo poweris plotted in standard deviations versus Doppler frequency relative to the estimated frequency of echoesfrom the Moon’s center of mass. The pattern of thespectrum shape is seen to be repeated at two independent stations, suggesting a high accuracy of the measurements.
By calculating radial velocity of the Moon relative to the transmitting antenna and the receiving antennas, the computed Doppler frequency shift for eachof the reception points was obtained. The experimental
Doppler frequency shifts were determined by the spectrum maximum frequency in bistatic mode. According
to the results of spectral processing of data, recorded at
Kunming RT-40, the series of Doppler frequency shifts
were measured for the Moon. As a whole, the measured Doppler shifts are in good an agreement withthe calculated values from the lunar ephemeris. Fig. 3
displays the difference of calculated and experimental

136

Sun et al.

0.15

40
SC
OC
δ F_doppler /Hz

Amplitude /rel. units

SC
OC
0.1

0.05

20

0

−20

0

−50

0
Frequency /Hz

−40
2.5

50

3
Epoch /hour (UTC)

3.5

Fig. 1: Opposite- and same-circularization continuous wave

Fig. 3: The difference of measured and calculated Doppler fre-echo power spectra of the Moon obtained with the Kunming RT40 at 02:50:00 UT on Apr. 26, 2019. The frequency resolution is
1.0 Hz.

quency shifts at Kunming RT-40 between 02:30:00 to 03:00:00
UT on April 26, 2019.

100
0.015
OC
Spectrum width /HzAmplitude /rel. units

80
0.01

0.005

60

40

20

0

2.6
−50

0
Frequency /Hz

50

Fig. 2: Opposite-circularization continuous wave echo power

2.7
2.8
2.9
Epoch /hour (UTC)

3

Fig. 4: Variation in the width of the reflected signal power spec-

spectra of the Moon obtained with the Sanya RT-13 at 02:50:00
UT on Apr. 26, 2019. The frequency resolution is 1.0 Hz.

tra with time. The filled and open circles mark the spectrum
widths for the Kunming RT-40 and Sanya RT-13 at the corresponding times, respectively.

Doppler frequency shifts at Kunming RT-40. The observations of the Doppler shift of the reflected signal
frequency were obtained, and the mean-root-square error is around 5 Hz in this experiment.
The power spectrum bandwidth as function of time
can be used for obtain the spin period in case of longobservation series. For all the received stations, thespectrum broadening of the echo signal reflected from
the Moon was less than 100 Hz. In Fig. 4, the filled andopen circles mark, respectively, the spectrum widths

for the Kunming RT-40 and Sanya RT-13 at the corresponding times. The measurement starts from 02:30:00
UT on April 26, 2019 and lasts for 30 minutes. The
profile line width is determined by the rotation of the
Moon’s reflecting surface, while its change is indicative of the shape asymmetry.
Circular polarization of the signal is reversed after reflection from the plane surface and the maximum
power of the reflected signal is expected in the OC
polarization, though some of the signal, due to sec-

Promoting Radar Astronomy

137

0.2

Amplitude /rel. units

SC
OC
0.15

0.1

0.05

0
2.5

3
Epoch /hour (UTC)

3.5

If the object is illuminated with a noise or the LFMsignal for a given mode, the spatial delay is measured.
This delay represents the time difference of the signal
propagation from the object to the two receiving telescopes and it is determined from the angular coordinates of the object. We also consider the processing ofnoise or LFM-signal with significantly lower signal-tonoise ratio than in the case of monochromatic signal.
In future, the bistatic radar observations of thepotentially dangerous asteroid during its close approach to the Earth will be carried out. And the precise
measurement of ephemeris of space debris fragments
are important for the prognosis of the dangerous
approaches with operational satellites.

Fig. 5: The spectrum amplitude obtained at Kunming RT-40 with

SC and OC, respectively.

ondary reflections, is received with the same polarization. The ratio of SC to OC is a measure of near-surface
wavelength-scale roughness (Bondarenko et al., 2017;
Ipatov et al., 2016). In our case, this quantity µC (circular polarization coefficient) is µC = 0.688 for Kunming
RT-40 and µC = 0.655 for Jilin RT-13. Fig. 5 shows the
spectrum amplitude obtained at Kunming RT-40 with
SC and OC, respectively.

4 Conclusions and discussions
The signal transmitted at X band with the domestic
radar and reflected from the Moon was successfully received with the radio telescops of the Chinese VLBI
Network. Obtained results confirm the possibility andeffectiveness of the bistatic radar observations of theMoon using radio telescopes of the CVN as receiving
part of a bistatic configuration. It was shown that receiving and processing of the continuous wave echo
allows to estimate the value of the Doppler frequency
with sufficient accuracy. Following this positive experience we plan to continue the interference frequency
in VLBI mode. The multiplication of signals, recordedin two VLBI-stations, will be carried out to measure
the frequency of the interference (fringe rate), which
depends on the angular velocity of the investigated object.

Acknowledgements This study made use of data collected
through the CVN (Chinese VLBI Network). The authors
wish to thank the staff of radio telescopes and radar team forparticipating in the experiments. The authors thank the National
Natural Science Foundation of China (NSFC) for funding
projects 11833001 and 11603001.

References
Bondarenko Yu, Medvedev Yu, Vavilov D, et al. (2017) Radarobservations of near-Earth Asteroids using the Quasar VLBI
Network Telescopes. European Planetary Science Congress
2017, 11
Ipatov A, Bondarenko Yu, Medvedev Yu, et al. (2016) Radar Observations of the Asteroid 2011 UW158. Astronomy Letters,
42, 12, 850–855, doi:10.1134/S1063773716120021
Molotov I, Nechaeva M, Falkovich I, et al. (2008) Astrometry of
the Solar System Bodies with VLBI Radar. In: A. Finkelstein, D. Behrend (eds.): IVS 2008 General Meeting Proceedings, 30–34
Nechaeva M, Antipenko A, Bezrukov V, et al.(2013) An Experiment on Radio Location of Objects in the Near-Earth Spacewith VLBI in 2012. Baltic Astronomy, 22, 35–41
Nechaeva M, Dugin N, Antipenko A, et al. (2015) VLBI
Radar of the 2012 DA14 Asteroid. Radiophysics and Quantum Electronics, 57, 10, 691–699, doi:10.1007/s11141-0159555-8
Ostro S (2007) Planetary radar. Encyclopedia of the Solar System, 735–764.
Tuccari G, Molotov I, Volvach A, et al. (2006) e-NRTV - Radar
VLBI Network LFVN. In: D. Behrend, K. D. Baver (eds.):
IVS 2006 General Meeting Proceedings, NASA/CP-2006214140, 236–240

Observations of Radio Sources Near the Sun
O. Titov, S. Lambert, B. Soja, F. Shu, A. Melnikov, J. McCallum, L. McCallum, M. Schartner, A. de Witt,
D. Ivanov, A. Mikhailov, S. O. Yi, W. Chen, B. Xia, M. Ishigaki, S. Gulyaev, T. Natusch, S. Weston

Abstract Geodetic Very Long Baseline Interferometry (VLBI) data are capable of measuring the light
Oleg Titov
Geoscience Australia, PO Box 378 Canberra, AU-2601 Australia
Sébastien Lambert
SYRTE, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université, LNE, Paris, France
Benedikt Soja
Jet Propulsion Laboratory, California Institute of Technology,
4800 Oak Grove Drive, Pasadena, CA 91109, USA
Fengchun Shu · Wen Chen · Bo Xia
Shanghai Astronomical Observatory, 80 Nandan Road, Shanghai, 200030, China
Alexei Melnikov · Dmitrii Ivanov · Andrei Mikhailov
Institute of Applied Astronomy, Kutuzov Embankment, 10,Saint-Petersburg, RU-191187, Russia
Jamie McCallum · Lucia McCallum
University of Tasmania, Private Bag 37, Hobart, Tasmania, 7001,
Australia
Aletha de Witt
Hartebeesthoek Radio Astronomy Observatory, PO Box 443,
Krugersdorp, 1740, South Africa
Matthias Schartner
Department of Geodesy and Geoinformation, Research Group
Advanced Geodesy, TU Wien, Gußhausstraße 27–29/E120.4,
Wien, AT-1040, Austria
Sang Oh Yi
National Geographic Information Institute, Space Geodetic Observatory, Sejong, PO Box 30060, South Korea
Masafumi Ishigaki
Geospatial Information Authority of Japan 1, Kitasato, Tsukuba
305-0811, Japan
Sergei Gulyaev · Tim Natusch · Stuart Weston
Institute for Radio Astronomy and Space Research, Auckand
University of Technology, Auckland, 1010, New Zealand(Correspondence: oleg.titov@ga.gov.au)

deflection caused by the gravitational field of the Sun
and large planets with high accuracy. The parameterγ of the parametrized Post-Newtonian (PPN) formalism estimated using observations of reference radiosources near the Sun should be equal to unity in thegeneral relativity. We have run several VLBI experiments tracking reference radio sources from 1 to 3 degrees from the Sun. The best formal accuracy of theparameter γ achieved in the single-session mode is lessthan 0.01 percent, or better than the formal accuracy
obtained with a global solution included all available
observations at arbitrary elongation from the Sun. We
are planning more experiments starting from 2020 using better observing conditions near the minimum of
the Solar activity cycle.

Keywords VLBI · General relativity · Ionosphere

1 Introduction
In accordance with General Relativity the radio waves
slow down due to the gravitational potential of the Sun(the so-called Shapiro effect; see Shapiro, 1964, 1967),
making very long baseline interferometry (VLBI) a
useful tool for testing General Relativity by meansof the parameterized post-Newtonian (PPN) formalism(Will, 1993). Nevertheless, the accuracy of the PPN parameter γ obtained from absolute or differential VLBI
observations (Fomalont et al, 2009; Lambert and Le
Poncin-Lafitte, 2009, 2011) remains worse than thecurrent best limit of (2.1 ± 2.3) × 10−5 based on Cassini
radio science experiment (Bertotti et al, 2003) by anorder of magnitude. The upper limits on the parameter
138

Observations of Radio Sources Near the Sunγ have been improved substantially in the past 30 years(Robertson and Carter, 1984; Robertson et al, 1991;
Lebach et al, 1995; Fomalont and Kopeikin, 2003),
but some authors (Shapiro et al, 2004; Lambert andLe Poncin-Lafitte, 2009) found degradation in the estimates of γ with elongation, and suggested that this systematic effect may limit the improvement in the VLBIderived γ upper limits, despite the dramatic growth in
the number of observations in recent decades.
The current paper focuses on radio source approaches at angular distances less than three degrees
from the centre of the Sun in order to measure the lightdeflection effect at the highest magnitude and, thus, toavoid a possible bias caused by observations at larger
elongations. We report on two special VLBI sessions,
AUA020 (May 2017) and AOV022 (May 2018), on
the single-session estimates of γ.

2 DataA dedicated geodetic VLBI experiment (AUA020, 0102 May, 2017, part of AUSTRAL program) was scheduled to probe the gravitational delay effect using a network of seven radio telescopes (Svetloe, Zelenchukskaya, Badary, HartRAO, Seshan25, Sejong, and Hobart26). Two radio sources 0229+131 and 0235+164
were observed at range of angular distances from 1.15◦
to 2.6◦ from the Sun. The position of both radio sources
with respect to the Sun at the start of the experiment isshown on Fig. 1. A serious issue in such a configuration is the solar thermal noise that penetrates to the signal through the side lobes, and could cause loss of data
due to striking the signal-to-noise ratio. To overcome
the problem, one has to1) select strong radio sources with larger correlated
flux density in both frequency bands,
2) use large radio telescopes with narrow side lobes
and better sensitivity, and
3) use the highest possible data rate recording (e.g.,
1 Gbps) to gain a better signal-to-noise ratio during thesame integration time.
More details about the schedule design are published in (Titov et al, 2018).
The target radio source 0229+131 is a defining
source of the ICRF2 whose position is given with anaccuracy close to the ICRF2 noise floor of 40 µas. The
position of the second target 0235+164 is less accurate

139

Fig. 1: Geometry of the radio sources close to the sun at thestart (Left) and at the end (Right) of VLBI session AUA020 withrespect to a LASCO C2 image of the solar corona. The Sun ishidden behind the occultation disc of the coronagraph, with thewhite inner circle representing the limb of the Sun. The field-ofview is 1.5 degrees elongation.

by a factor of five but still at the level of the ICRF2
median error and largely below the millisecond of arc.
Both sources are compact and their structure indicesmeasured at the time of the ICRF2 work were of 2.4
and 1.3, respectively, ensuring a structure delay lower
than 2 ps (Fey and Charlot, 1997).

3 Analysis and Results
For purpose of cross-checking the results and testing
their robustness, we processed the VLBI session
AUA020 within two independent teams with two independent geodetic VLBI analysis software packages.
The duplication of the analyses with two software
packages also allows to use some specific options thatare available on only one of them. The first analysis
package is OCCAM (Titov et al., 2004) that implements the least-squares collocation method (Titov,
2000) for calibrating the wet troposphere fluctuations,and to account for the mutual correlations between
observables. The second one is Calc/Solve (Ma et al.,1986), developed and maintained by the geodetic
VLBI group at NASA GSFC, that uses classicalleast-squares. More details about the data analysis
design are discussed in (Titov et al, 2018)
Table 1 shows the results of the AUA020 experiment data analysis. Uncertainties on γ lie between
0.9 × 10−4 and 4 × 10−4 . Our estimates appear therefore
as precise as that obtained from global solutions using thousands of VLBI experiments (Lambert and Le
Poncin-Lafitte, 2009, 2011). The formal error is about
two times lower when γ is fitted to the observations of

140

the radio source that is two times closer to the centreof the Sun (0235+164) than to that of its counterpart(0229+131). Using all scans returns a result similar tousing only scans relevant to 0229+131 and 0235+164,
confirm that only sources a low elongation can efficiently constrain the PPN parameter. Solutions fromboth software packages are consistent within the standard errors. The difference of postfit rms between OCCAM and Calc/Solve might find its origin in the different modeling of the nuisance parameters (stochastic
versus CPWL function). No large systematics are detected except a 2.7σ deviation in the Calc/Solve solution when only 0229+131 is used and whose origin is
unclear: as both solutions started from the same a priori, the issue could rather be in the estimation method
or in the handling of troposphere/clock parameters.
It appears that during session AUA020, data inthree channels at Sejong station were lost due to technical reasons. Therefore, we reprocessed the previous
analyses after downweighting (but not suppressing) Sejong data. (We could test this option with OCCAM
only since Calc/Solve does not handle downweighting.) The postfit rms of the solution is significantly lowered. The formal error on γ is marginally lowered down
to 9 × 10−5 .
For purpose of comparison of the AUA020 session
with other standard geodetic VLBI sessions, we estimated γ with Calc/Solve using the parameterization
described above for each of sessions of the full geodetic VLBI data base made available by the International
VLBI Service for geodesy and astrometry (IVS) since
1979 (at the exclusion of intensive sessions). The median postfit rms is 27 ps that is close to the postfit rms of
the AUA020 session. The distribution of the obtained
values of γ − 1 is shown in Fig. 2 along with distributions of errors and normalized estimates. The distribution of errors in log-scale is slightly asymmetric,
exhibiting a ‘tail’ on its right side that might traduce
results from sessions not designed for precise astrometry. Nevertheless, assuming a Gaussian shape, the logscaled distribution peaks at 10−2 with a σ of ∼ 0.5. This
makes the error estimate from AUA020, that is two orders of magnitude less, somewhat ‘outstanding’. The
bottom-right panel of Fig. 2 shows that the major partof the sessions does not bring severe systematics, theestimates of γ being unity within the error bars; session AUA020 is part of the session group that presents
the lowest systematics.

O. Titov et al.
Table 1: Estimates of γ − 1 for the session AUA020, in unit of

10−4 , along with the session χ2 and the postfit rms delay r in ps.
γ − 1 σγ10−4 10−4χ2 r

All stations

OCCAM

All scans 0.56 1.15 0.34 28
0235+164 1.34 1.58 0.34 28
0229+131 −1.54 3.41 0.34 28
Both 0.53 1.14 0.34 28
With Sejong downweighted
All scans
0235+1640229+131
Both

0.91 0.94 0.27 21
1.64 1.29 0.27 21
0.32 2.83 0.27 21
0.89 0.94 0.27 21

All sources −0.22 1.10 0.84 26
0235+164 1.85 1.48 0.84 26
Calc/Solve0229+131 −6.84 2.53 0.84 26
Both −0.26 1.09 0.84 26

Fig. 2: Distributions of (Top) estimates of γ − 1, (Bottom-left)
their formal errors, and (Bottom-right) normalized estimates ofγ − 1 for all of the geodetic VLBI sessions. The vertical, red bar
stands for the results of the AUA020 session.

Another experiment (AOV022) was undertaken on
01-02 May, 2018 with ten radio telescopes (Svetloe,
Zelenchukskaya, Badary, Hobart26, Seshan25, Kunming, Ishioka, Yarragadee, Katherine, Warkworth).
The same radio sources (0229+131 and 0235+164)
were scheduled with the same strategy. The statisticsof the result was found to be 2-3 times worse than from
AUA020, presumably, due to severe source structure
delay effect. Fig. 3 shows the post-fit residuals of forradio source 0229+131 for two baselines, IshiokaSeshan25 and Badary-Zelenchk. The variations of theresiduals are consistent to the variations induced by

Observations of Radio Sources Near the Sun

Fig. 3: Post-fit residuals of 0229+131 with baselines Ishioka-

Seshan25 and Badary-Zelenchk.

the source structure (Titov and Lopez, 2018) therefore,
we believe, that more detailed analysis is required toobtain a better statistic for this experiment.

4 Conclusions and outlook
In this paper we discuss our results on testing of general relativity with geodetic VLBI using the close approach of the Sun to the reference radio sources. It wasa general misconception in the past that the effect ofthe plasma of the solar corona completely disturbs theinterferometric responce for light rays passing withinseveral degrees from the Sun. We proved that these perturbations are at an acceptable level unless the signals

141

pass active streamers in the solar corona. Therefore,
the standard dual frequency calibration facilitates thestochastic noise induced by charged particles the solar
corona by the same way as for the ionosphere aroundthe Earth.
While the systematic effects based on radial or
dipole models of the corona appear to be negligible, individual group delay observations are affected by random scatter caused by small-scale coronal structure
and temporal variations thereof. Since these perturbations do not systematically affect the observations, we
assume that they cancel out over the period of observations (17 hours with observations angularly close
to the Sun). Since the ray paths to the radio sources
0235+164 and 0229+131 within small solar elongation
happened to be in quiet regions (cf. Fig. 1), the scatter
was small enough that precise group delays could be
successfully determined at such small elongations.
The major source of stochastic noise in VLBI measurements resides in the unknown wet troposphere delay. The difference between VLBI estimates of the wet
troposphere delay and independent radiometer data appears to stay within 3 mm, or 10 ps (Titov and Stanford,2013) suggesting that the impact of the wet tropospheredelay on the astrometric light deflection angle estimation near the Sun is negligible.
Overall, a total improvement of the uncertainty on
γ by a factor of ten is expected, enabling to challenge
the current limit imposed by the Cassini radio science
experiment of Bertotti et al (2003), although the Gaia
astrometry on Solar system objects is expected to deliver an accuracy of 10−6 (Mignard and Klioner, 2009).
Acknowledgements This paper is published with the permission of the CEO, Geoscience Australia. B. Soja’s research was
supported by an appointment to the NASA Postdoctoral Program, administered by Universities Space Research Association,at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with National Aeronautics and Space
Administration. We are grateful to D. Gordon (GSFC) for postprocessing reduction of the AUA020 data.

142

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Autonomous Observations of VLBI Radio Telescopes
A. Neidhardt, E. Barbieri, J. Bachem, M. Schönberger, M. S. Hameed, L. Carlin, R. Aktas, S. Jingyao,
A. Szomoru

Abstract Current techniques in software and hardware
allow, to increase the automation of systems. An autonomous, state-driven processing of VLBI schedules
from autonomous fetching and preparation of schedules, the operation of observations and the finalization and transfer of data is possible. Industrial monitoring suites allow a centralized overview, so that a reduced number of operators can quickly get the statusof several instruments. Historic values allow the analysis of failure situations and their causes. To increase
the automation and to even support autonomous observations, updates and tests are ongoing at the Wettzell
observatory.

Keywords Automation · Monitoring · Centralized
Network Overview

1 Introduction
Several years ago, implementations started to convert
manual tasks of VLBI observation to more automatedworkflows. Improvements were identified amongst
Alexander Neidhardt
FESG Wettzell, TU of Munich, Geodetic Observatory Wettzell,
Sackenrieder Str. 25, DE-93444 Bad Kötzting, Germany
E. Barbieri · M. S. Hameed · L. Carlin · R. Aktas · S. Jingyao
FESG, TU of Munich, Arcisstr. 21, DE-80333 Munich, Germany
J. Bachem · M. Schönberger
BKG, Geodetic Observatory Wettzell, Sackenrieder Str. 25, DE93444 Bad Kötzting, Germany
Arpad Szomoru
Joint Institute for VLBI ERIC, Oude Hoogeveensedijk 4, NL7991 PD Dwingeloo, The Netherlands(Correspondence: neidhardt@fs.wettzell.de)others in optimized networks (re-arrange VLBI networks in failure situations with dynamic observing
modes, Lovell, 2016), better data quality becauseof defined processes instead of operator-individual
behavior, and reduced requirements of manpower for
operator shifts (Neidhardt, 2017, page 505 f). While
it is easy to automate some specific tasks, like downloading a new schedule or starting a new schedule asinvocation of the according file in the NASA Field
System, other steps were challenges, like detecting andreacting on failure situations, generating automatedmeteorological descriptions, or recording data withoutchanging VLBI modules. Meanwhile, technique andhardware improved. For example, Digital Baseband
Converters are able to use formatters streaming data
directly via 10 GBit/sec networks to storage servers(like Flexbuff systems). Industrial monitoring systems
improve the collection of innumerable parameters
about system health directly evaluating critical situations. A wide field of meteorological devices (likeNubiscopes for cloud coverage, rain sensors, snow
sensors, etc.) extend information from elementary
meteorological stations to produce quantitative, textual descriptions of the prevailing weather situation.
Therefore, even complete autonomous observation areclose enough to touch.
Ideas at the Wettzell observatory started early to implement such autonomous observations. The final goalis, to automatize all steps of a VLBI observation, sothat at least no operator is required anymore. The operations include:
1. Autonomous checking for sessions on the different
repositories
2. Prioritization and planning of local observations ofsessions
3. Autonomous fetching of session schedules
143

144

4. Local preparation (drudg) without human interaction
5. Local adaption and recorder selection according
predefined specifications
6. Automatic start-up of local observations
7. Frequent notification and monitoring of observation status
8. Continuous quality control and alarm management
9. Individual post-processing and archiving data andmeta-data
In a final development state, external partners mightinteract with the local control system to adapt session
parameters and continuously get information about internal processes while the system makes its own decisions to control devices according to individual feedback from sensors. This state can be seen as an implementation of a ”smart observatory”
Programs and scripts at the Wettzell observatory
are tested to support these automated tasks. A special
setup even enables monitoring and controlling of theNASA Field System and station-specific parts. Centralized displays permanently show health states, so thateven staff of the observatory guard can check and interpret system situations.

2 ”Automating” the NASA Field System
Most antennas of IVS network use the NASA Field
System to control individual equipment. The system
originally was written in FORTRAN but greatly extended with C code. The system is a more or less loose
coupled arrangement of programs running parallel tointerpret commands, control hardware, monitor systemstatus, interact with the user, and report errors, supervised by a central program, called ”boss”. The wholeobservation is controlled with a predefined batch file,activating tasks when time reaches predefined timetags. This simple sequential flow is already an automated processing, but has the disadvantage that checks
and error reports are only created when time-tags define them (Neidhardt, 2017, page 409 f), and that local
programs are responsible for keeping healthy states forthe antenna and equipment.
Completely autonomous systems require continuous monitoring of health states to make decisions immediately in case of alerts or critical situations during observations (critical situations for humans are protected by the system hardware itself, which is certified

Neidhardt et al.

by companies). As so many antennas use the Field System, programs for autonomous operations must include
the existing version of the Field System. This requires
a mechanism to manage user interaction with the Field
System to interpret and quantify them. Additionally,
sensors and actors which are usually directly connectedto the Field System must be permanently monitored
and partly controlled in parallel to the Field Systemcommanding.
Mechanisms to do this are known from software
testing of legacy programs (see Fig. 1), where existing code should be treated with error situations to measure the reactions. To do this, hardware or equipment
is represented with software stubs, which communicate to both, the system under test on the one hand
and the hardware on the other hand. User interactions
are forced with mock objects playing the role of a user
and feeding commands to the system while listening to
responses. Exactly this setup can be used to increase
the automation of the VLBI control using the existing NASA Filed system without touching it. The userinteractions are managed with the already existing eRemoteCtrl server originally developed to control telescopes remotely. Therefore, e-RemoteCtrl can alreadybe seen as mock object. Interfacing the hardware is implemented with software-generated stubs offering highsafety and reliability.
e-RemoteCtrl is a client-server system connecting
the NASA Field System shared memory to monitor internal parameters, Ettl et al. (see 2012). Additionally,log files are read and interpreted to get current status information. Commands can also be sent using theNASA Field System mechanism to inject specific Field
System commands to ”boss”. For the Wettzell monitoring system, IVS seamless auxiliary data archive, and acentral monitoring system located at JIVE and part ofJumping JIVE project funded by the EU Horizon 2020
framework, e-RemoteCtrl was extended with an elementary web server. It simplifies interaction with theField System using predefined template HTML pages
where current system values are dynamically set. The
values are tagged with HTML comments to find themagain in the web pages later on by automated, external
processes.
Software generated stubs use a mechanism described in Neidhardt (2017, page 148 f). The complete
framework is defined and generated during a domain
engineering process where all parts generally relevant
for all stubs are programmed. Application specificAutonomous Observations

parts are described with a meta-program in a specificdomain specification language, so that a software generator produces the final program taking general parts
and adapting them to specific applications. Advantages
are the well-tested domain part, the flexible adaption,and especially the always existing and stable safetymechanisms from the domain software.
Each stub program runs an application process anda watchdog process. The watchdog permanently controls, if the application is still running and available.
The application process is split in one control and communication flow and several parallel processing lines
communicating with the hardware and organized as
POSIX threads. This architecture avoids time delay
propagation from hardware to the Field System, keeps
processes accessible, and allows a separate data extraction for additional monitoring features. It builds a monitoring bypass to the NASA Field System line, so thatsystem health states can be controlled continuously.

3 Using the data from the monitored(NASA Field) System
While the dynamic web pages from e-RemoteCtrl canbe used locally by operators with each type of Inter-145

net browser, and monitoring data from the bypass canbe used with local scripts and programs to make decisions, such data can also be collected from centralized services. Therefore, a central monitoring serverfor VLBI health data was installed using the monitoring suite ZABBIX (Zabbix, 2018). The server is a
HPE ProLiant DL380 Gen10 8SFF with 6.5 TB effective RAID volume. It runs the ZABBIX suite, a PostgreSQL database, an Apache2 web server, and several
scripts and programs to fetch, extract and process datafrom the NASA Field Systems of the Wettzell antennas(Wz, Wn, Ws, Oh, and AGGO). Antennas individuallyconnect to the server using SSH reverse tunnels, so thatthe server is able to access the NASA Field Systemmonitoring web pages on the site-specific Field System PC. Additionally, SNMP and ZABBIX agents areused to monitor server components, UPS power supplies, rack cooling, temperature sensors, and so on. Alldata are stored in the database for three month. If data
should be archived, they can be extracted to text files
using Python scripts. Some ZABBIX mechanisms areunder test to extract information also from log files.
ZABBIX offers dynamic web pages to show thehistory of data in line plots, pie charts, and othergraphs, which can be defined by the system administrator. Additionally, ZABBIX maps and screens can be

Fig. 1: A method to get system health states parallel to the NASA Field System.

146

Neidhardt et al.

Fig. 2: The data flows from local monitoring sources to central data servers offering a complete VLBI network status.

used to show interactions and logic structures of thesystems which are monitored combined with diagramsor single information. Operators are able to selectspecific time intervals of interest just by selecting
the individual part in the diagrams with the mouse.
Different user environments allow individual viewsof the data, so that operators get specific, detailed
data sets, while for example a guard at the gate of
the observatory just gets an overview of health states
on a station map presented with an Android XOROMegaPAD.
Important is the include mechanism of triggers. Administrators set trigger levels or logical combination of
trigger levels which are use to fire alerts. The Wettzell
system uses three different levels of severity: warnings about reduced data quality (blue color code), errors about reduced or lost data (yellow color code), andalerts about situations when hardware or humans are indanger (while ZABBIX is a pure monitoring systemshowing health states, so that the hardware itself andlocal regulations must protect humans from danger).
Besides Wettzell specific presentations for an observatory monitoring and risk management, status information is also combined to global network maps for
European VLBI Network (EVN) and IVS, while cur-rently only test sites are included. A world map shows
all sites and their status information, so that a centralized operator can see if one of the participating telescopes has problems. Currently dynamically adapted
maps are under test to present maps just showing stations participating at the current session.
Combined with standardized data senders at theantenna sites using e-RemoteCtrl, a standardized data
flow is realized, which offers a global overview of network situations and its history (see Fig. 2).

4 Towards a data achive for seamlessauxiliary data

Having an existing central VLBI network monitoring,data of interest for analysts can also be extracted into
text files to create an archive for seamless auxiliarydata. Using a Python script written during the project
Jumping JIVE, several sensor data can be extracted.
Currently of interest are especially meteorological values, to keep them continuously and not just session related for the time of an active session. The result ofsuch an extraction is shown in Fig. 3

Autonomous Observations

147

Fig. 3: Extracted seamless, auxiliary data of one sensor.

5 Conclusions and outlook
The monitoring system of the VLBI antennas at theWettzell observatory changed from the test hardware
to the final productive database server. It has been successfully active for several month. Found bugs are repaired. The data stock allows support of maintenancework, like during cold-head replacements at the cryogenic dewar. It is a support for remote diagnostics forthe experts. Additionally, the tablet at the guard of
Wettzell is used to identify and present critical system
states.
This was successfully shown in case of a power
failure during storm ”Eberhard” on March 10th, 2019from 18:09 till 18:30 UTC (see Fig. 4). The storm
caused a short power outage for the region which resulted in a chain of problems, keeping the UPS in battery mode. Without detection, the whole data centerfor the Wettzell telescopes would run out of power after finishing the power from the batteries. Additionally,
water cooling of the racks failed. Because of the notification service of the monitoring system, the guard was
informed and was able to reactivate everything guided
by an expert on the phone. Besides this power failure
several wind stow alerts also demonstrated that the automatic stow alert works well enough to use it for automatic antenna shutdowns in case of storm situations.
The current limit is 70 km/h even if all antennas would
be able to work until max. gusts of 130 km/h.
This local monitoring is going to be extended anda first autonomous operation during night shifts isplanned for September 2019. It would be necessary to
motivate other antennas also to provide auxiliary data
for the archive to establish a global data monitoringand seamless, auxiliary data archive.

Fig. 4: Remaining charge in percent of the UPS (a) and windstow alerts (b) during storm ”Eberhard”.

Acknowledgements This project has received funding from theEuropean Union’s Horizon 2020 research and innovation programme under grant agreement No 730884 - JUMPING JIVE.

References
Ettl M, Neidhardt A, Schönberger M, et al. (2012) e-RemoteCtrl:
Concepts for VLBI Station Control as Part of NEXPReS;
In: D. Behrend, K. D. Baver (eds.): IVS 2012 General Meeting Proceedings, NASA/CP 132, National Aeronautics andSpace Administration
Lovell J, Plank L, McCallum J, et al. (2016)
Dynamic
Observing with the AuScope VLBI array 5th International VLBI Technology Workshop - MIT Haystack Observatory, https://www.haystack.mit.edu/workshop/ivtw2016/
presentations/jlovell ivtw2016.pdf, Download 2018-09-17
Neidhardt A (2017) Applied Computer Science for GGOS Observatories. Communication, Coordination and Automationof Future Geodetic Infrastructures. Springer International
Publishing Switzerland, doi:ISBN 978-3-319-40137-9
Zabbix LLC The Ultimate Enterprise - class Monitoring Platform https://www.zabbix.com/, Download 2018-09-13

Mixed-mode VLBI Experiment with Chinese Stations in
APSG40
X. He, F. Shu, W. Jiang, L. Ma, X. Yang, L. Chen

Abstract Asian Pacific Space Geodynamics (APSG)
geodetic VLBI sessions are being regularly performed
within the IVS to improve the accuracy of the geocentric coordinates of the participating stations in the
Asia-Pacific region. In the experiment APSG40, we
conducted mixed-mode observations with participationof 4 Chinese stations which have no standard geodetic
recording mode available. Among them, the Chinese
deep space stations located at Jiamusi and Kashi have
only 100 MHz bandwidth at X and S-band respectively,
and the two small antennas located at Jilin and Sanya
have a wide frequency coverage of 1.2 − 9.0 GHz. The
observational data have been correlated and analyzed.
For the first time we derived the coordinates of Jilin
and Sanya at 1 cm level by geodetic VLBI. Here we
present the experiment setup, data processing method
and initial results.

Keywords VLBI · Mixed-mode observations · Station
coordinates

Xuan He · Fengchun Shu · Wu Jiang
Shanghai Astronomical Observatory, Chinese Academy of Science
Langming Ma · Xuhai Yang
National Time Service Center, Chinese Academy of Sciences
Lue ChenBeijing Aerospace Control Center(Correspondence: hexuan@shao.ac.cn)

1 Introduction

One goal of VLBI technique is to determine stations’coordinates which can be served as fiducial points ofglobal geodetic reference frame. Accurate positions of
VLBI stations are also essential for phase referencing
astrometry and deep space navigation.

In 2013, two Chinese Deep Space Network(CDSN) stations, Jiamusi 66-m antenna and Kashi
35-m antenna, have been built. Each of them isequipped with a narrow-band S/X receiver covering the frequency range 2200 − 2300 MHz and
8400 − 8500 MHz. More recently, two small antennas
with 13-m aperture have been deployed in Jilin andSanya by the National Time Service Center (NTSC).
They are equipped with a broadband receiver witha frequency coverage between 1.2 and 9 GHz. The
received signals are combined and converted into rightcircular polarization. Currently only 2 bands can beacquired using digital backends in PFB mode.

Asian Pacific Space Geodynamics (APSG) geodetic VLBI sessions are being regularly performed in order to improve the accuracy of the geocentric coordinates of the participating stations in the Asia-Pacific region. In the APSG40 session, the 4 stations mentioned
above have been tagged along. In addition to standard
geodetic mode used by the APSG stations, another two
different modes were used by CDSN and NTSC stations. We report on the mixed mode experiment, dataprocessing method and initial results.
148

APSG Mixed-mode Experiment

2 Experiment
APSG40 is the 40th APSG session conducted on July25, 2017. A total of fourteen stations participated in
the 24-h S/X dual-band geodetic experiment. Those
stations are located on the four plates: Australian
Plate, Eurasian Plate, Pacific Plate and North America
Plate. Figure 1 shows the geographical distribution of
APSG40, CDSN (Jiamusi and Kashi) and NTSC (Jilin
and Sanya) stations. The primary purpose of this Asian
Pacific Space Geodynamics (APSG) session is tocontinue monitoring the relative motions of the plates
in the Asia-Pacific region. In addition, we planned
to determine the precise positions of four Chinese
stations which have no standard geodetic recording
mode available.

149

the range of [8.1, 8.6] GHz, and 4 IFs at the frequency
range of [2.2, 2.3] GHz. Two terminals were used torecord X-band data with a 2 Gbps rate and S-band datawith a 512 Mbps rate respectively.
To make it clear, Figure 2 shows APSG40, CDSN
and NTSC stations X band frequency sequences withrespect to 8181 MHz. The bandwidth for each IF channel is 8 MHz for APSG and CDSN stations, and 32
MHz for NTSC stations.

Fig. 2: X-band Frequency sequence with respect to 8181 MHz.

Considering the CDSN has only 4 IF channels andthe APSG/NTSC has 10 channels in common at Xband, we optimized the frequency sequence for bothcases to get better delay resolution function whichshowed in Figure 3. The delay ambiguity is 62.5 µs,
while the sidelobes of the DRF are less than 0.6.
Fig. 1: Geographical distribution of participating stations, where

CDSN and NTSC stations are shown in red circles.

The experiment was performed with mixed observing mode. SKED software was used for scheduling. We
selected 76 geodetic good sources distributed over thewhole sky. Except for Kashi and Jiamusi, the other stations have more than 200 scans. The sub-array option
was used to assure that the target sources have a better
coverage over the local sky of each station.
Ten APSG40 stations have 10 IF channels at thefrequency range of [8.2, 8.6] GHz, and 6 IFs at therange of [2.2, 2.3] GHz. The corresponding data rate is
512 Mbps. But two CDSN stations have only 4 IFs at
the range of [8.4, 8.5] GHz and 4 IFs at [2.2, 2.3] GHz.
The corresponding data rate is 256 Mbps. Moreover,
two NTSC stations have 16 IFs at the X band spread in

Fig. 3: X-band Delay Resolution Function for two frequency se-quences.

150

3 Data processing
3.1 Data correlation
Data correlation of the experiment was performed at
the Shanghai VLBI Correlator. Since the recording
bandwidth and the frequency coverage were different
among APSG, CDSN and NTSC stations, the zoom
mode in the DiFX correlator was used to extract thefrequency channels in common with APSG stations.
We correlated the data in three different passes: APSG
station only, APSG+CDSN stations, APSG+NTSC
stations. The DiFX correlator outputs in each passwere converted into FITS-IDI format for further
post-processing separately.

He et al.

Kashi are from Xu et al. (2016). Jilin and Sanya stations did not participated in geodetic VLBI observations before. We got their approximate positions withan error less than 10 cm derived from local survey.
Their velocities are considered to be 0. We chose Sheshan25 as clock reference. The estimated parameters
include clock, atmosphere, UT1-TAI, nutation, and coordinates of CDSN/NTSC stations.

4 Results
The Weighted RMS (WRMS) delay residuals for thebaselines to CDSN stations is 85.0 ps and for the NTSC
stations is 50.7 ps. Figure 4 shows the post-fit delay
residuals on the baseline Ishioka-Jilin and the WRMS
is 41.7 ps.

3.2 Post-correlation processing
The FITS-IDI files were loaded into PIMA (Petrov
et al., 2011), a post-processing software. Phase calibration was not applied to the four Chinese stations
because they have no good phase calibration signals
available. After running coarse fringe fitting, we
performed bandpass calibration. We checked thefringes before computation of a complex bandpass,and masked out cross-spectrum data whose amplitudeis less than 0.4 at the edges of each channel.
Finally we ran fine fringe fitting and export
database in GVF format for data analysis.

3.3 Data analysis
We used Psolve which supports databases in the GVF
to analyze this session. At this stage, we removed Kunming, Kashim11 and Koganei related baselines because those delay observables are very noisy. The S/X
combination solution after removing ionospheric effects can be applied to APSG and CDSN stations.
Unfortunately, Jilin and Sanya stations have very
low sensitivities at the S-band. Therefore only X-banddelay observables can be used. We had to apply GPS
ionosphere model to correct X-band delays. The apriori station coordinates and velocities for APSG stations are based on ITRF2014. Those for Jiamusi and

Fig. 4: Post-fit delay residuals on the baseline ISHIOKA –JILIN.

Table 1 shows the adjustments and precisions of
NTSC and CDSN stations on July 25, 2017. It can beseen that the precisions in UEN components for eachstation vary between 0.44 and 26.70 mm. The precisions of the vertical component is much worse thanthat of the other two components. The positions of Jilin
and Sanya have been determined with an error at 1 cm
level. Jiamusi and Kashi stations have narrower frequency coverage. Thus it produces less accurate delay
observables, which in turn causes larger uncertainties
of station coordinates.
As shown in Figure 5, we have derived observed
station SEFDs from fringe SNR information, except
for Kunming, Kashim11 and Koganei which had bad
performance. For APSG stations, only Urumqi had aAPSG Mixed-mode Experiment

151

Table 1: The adjustments and precisions of NTSC and CDSN stations.

Coordinates
U /mm
E /mm
N /mm

Jilin

Sanya

JiamusiKashi

adjustment σ adjustment σ adjustment σ adjustment σ−49.76 8.91
−58.10 12.58−53.59 26.56
17.23 26.70
24.64 1.87
101.36 2.53
52.94 8.87
35.70 0.44
24.98 1.57
−20.60 2.11
−0.73 6.05
106.65 5.93

Fig. 5: Estimated station SEFDs at S/X bands in APSG40.

worse X-band SEFD value than expected. The CDSN
stations had a similar performance as previous experiments. The NTSC stations had very high S-band
SEFDs, probably caused by the RFI. Because we correlated the lower edge of 32 MHz bandpass against with
8 MHz bandwidth of APSG stations, Jilin had a higher
SEFD at X-band. However, Sanya is still a bit noisy at
X-band.

5 Summary

The mixed-mode observations with participation offour Chinese stations in APSG40 has been performed.
We determined the positions of the two NTSC stations
at 1 cm level in geodetic VLBI experiment for the
first time. We demonstrate that those stations with
non-standard geodetic observing mode can be usedin geodetic experiments and their precise positions
can be determined, even though there is only X-band
available.

Acknowledgements This work is supported by the National
Natural Science Foundation of China (Grant No. 11573056).

References
Petrov L, Kovalev Y Y, Fomalont E B, et al. (2011) The VeryLong Baseline Array Galactic Plane Survey — VGaPS. AJ,
142, 35–35 doi:10.1088/0004-6256/142/2/35.
Xu D, Dong G, Wang G, et al. (2016)
First geodetic VLBI sessions with the Chinese Deep Space Stations Jiamusi and Kashi.
ASR, 58(9), 1638–1647
doi:10.1016/j.asr.2016.07.022.

Intensive Sessions with the Mauna Kea VLBA Station
C. Dieck, M. Davis, M. Johnson, J. Gipson, S. Byram, D. MacMillan

Abstract Due to its location on the Hawaiian Islands in the middle of the Pacific Ocean, the Mauna
Kea station (MK-VLBA) of the Very Long Baseline Array (VLBA) is well positioned for Intensive
sessions with stations in the continental UnitedStates, Western Europe, and East Asia, similar to
the Kōke‘e Park Geophysical Observatory (KPGO).
Recently, the International VLBI Service for Geodesy
and Astrometry (IVS) and the United States Naval
Observatory (USNO) initiated observing sessions
to characterize the MK-VLBA:WETTZELL and
MK-VLBA:WETTZ13N baselines to explore theirpotential as operational backup baselines for IVS Intensives. The USNO has also been using MK-VLBA in
similar sessions with other VLBA stations, particularly
PIETOWN, in its efforts to develop a VLBA-based,consistent, high quality UT1−UTC series for use
in EOP combinations. We present the status andperformance of these sessions, including the detectionof the MK-VLBA station displacement resulting
from the Kīlauea eruption and associated earthquake,and our plan to account for this displacement in themeasurement of UT1−UTC.

Keywords UT1−UTC · Intensives

Christopher Dieck · Maria Davis · Megan Johnson · Sharyl
Byram
United States Naval Observatory 3450 Massachusetts Avenue
NW, Washington, DC 20392 USAJohn Gipson · Dan MacMillan
NVI, Inc. / NASA Goddard Space Flight Center, 8800 Greenbelt
Road, Greenbelt, MD 20771 USA(Correspondence: christopher.dieck@navy.mil)

1 The W-Series: characterizing thebaselines from Mauna Kea to Wettzell

The IVS supports the International Earth Rotation
and Reference Systems Service (IERS) Rapid Service/ Prediction Center (RS/PC) by observing daily
Intensive sessions. Only three stations are currently
regularly used to make these observations (KOKEE,WETTZELL, and ISHIOKA). If more than one stationis unavailable at a given time no Intensive will beobserved, resulting in a degradation in the value of
UT1−UTC reported by the RS/PC. Such a situation
could occur in 2019 as both KOKEE and ISHIOKA
will be unavailable for extended periods of time
due to upgrades and maintenance, and these outages
may overlap. To ensure a high-quality UT1−UTC
product from the RS/PC, additional stations need to beprepared to be alternates.
Before a station can be considered part of the Intensive network, it must first make at least 60 test
observations with another station in the network overthe course of at least four months to characterize thatbaseline for use by the RS/PC (Davis et al., 2019).
The VLBA station on Hawai‘i at Mauna Kea (MKVLBA) is at the eastern end of the Hawaiian Islands,∼500 km south-east of KOKEE, and would therefore
be a good substitute for KOKEE when it is unavailable. Similarly, Wettzell North (WETTZ13N) is very
close to WETTZELL and could act as an alternate to
WETTZELL. With the goal of adding MK-VLBA andWETTZ13N to the network of Intensive-ready stations,
the RS/PC, USNO Analysis Center, and IVS Coordinating Center developed a series of test Intensives incoordination with the Geodetic Observatory Wettzell
152

MK-VLBA Intensives

to characterize the MK-VLBA:WETTZELL (MkWz)
and MK-VLBA:WETTZ13N (MkWn) baselines.
The IVS Coordinating Center determined that thesesessions would be named wYYDOY with the data basecode of XW (hence the name “W-series”). The backends of the VLBA and IVS S/X system are different,
preventing the standard IVS Intensive observing setup
from being used. The proven setup of the IVS RDV
sessions, which use both VLBA and IVS stations, wasthus employed. Though ideally each of the two baselines would have their own independent one hour Intensive session, the amount of time for such sessions was
not available on the VLBA. By merging with the 90minute Intensives that the USNO observes daily with
the MK-VLBA and PIETOWN stations, the MkWz,
MkWn, and MK-VLBA:PIETOWN (MkPt) baselines
could all be observed simultaneously. This resulted
in a four station network of MK-VLBA, PIETOWN,WETTZ13N, and WETTZELL being used for the Wseries.
Simulations showed that a 90-minute session withthe four stations would likely be sufficient to continue
to meet the USNO’s standards for the MkPt baseline
while also meeting the requirements for characterizing
the MkWz and MkWn baselines. Extending the sessions to 120 minutes ensured the required data quality while not exceeding the time allotted. Though IVS
Intensives are typically one hour long, two hour sessions do not interfere with the characterization of baselines designed to be used for one hour sessions. Any
reduction in the uncertainty due to the longer session length provides a more precise characterization
which will be utilized with any one hour Intensive observed after the characterization is complete. Furthermore, the UT1−UTC rate over that time period does
not have an appreciable effect on the parameter estimates or their uncertainties, as was verified in subsequent session analysis. Sessions are scheduled for the
MK-VLBA:WETTZELL baseline and then PIETOWN

153

and WETTZ13N are tagged along. The Geodetic Observatory Wettzell is able to support the sessions threetimes per week (only twice per week on WETTZ13N),
observed at fixed times. Specifics of the schedule canbe found in the IVS Intensive Master File.
As of June 30, 2019 there have been 54 successful sessions. The first few sessions had issues with the
WETTZ13N station setup in the schedules, and as aresult fringes were not found on baselines including
WETTZ13N. The observations will continue through2019 to accumulate the 60 observations required forbaseline characterization.
Table 1 shows the expected number of scans and
UT1−UTC formal error from the simulation and theresults from the W-series sessions. Residuals of the
USNO Analysis Center’s UT1−UTC measurementsfrom the W-series with respect to the reported values
from the RS/PC’s finals.all are shown in Figure 1
along with residuals from the KOKEE:WETTZELL
Intensives for reference. All indications to date are thatthe baselines from the Wettzell stations to MK-VLBA
will be viable backups to current operational baselines.

2 Mauna Kea displacement: detection
through Mauna Kea – Pie Town
Intensives
The USNO has been using the MK-VLBA station tomonitor the earth’s rotation for several years, primarily in conjunction with the PIETOWN station (Geiger
et al., 2019). The UT1−UTC measurements resulting
from these sessions have proven difficult to incorporate
into the products produced by the RS/PC. As a result,the USNO Analysis Center has been evaluating the
VLBA Intensive baselines to optimize a product thatcan be utilized by the RS/PC. In addition to exploring

Table 1: The comparison of the number of scans and the formal errors from the simulation of a single 90-minute schedule of

MkPtWz to medians of those metrics from the 54 120-minute MkPtWnWz W-series sessions observed through June 30, 2019.
90-minute Simulation
120-minute Sessions
UT1−UTC
Median # Scans Median UT1−UTC
Baseline # Scans Formal Error (µs) # Sessions per Session
Formal Error (µs)
MkPt
48
21.0
49
49
35.2
MkWn
–
–
22
18
15.5
MkWz
41
5.5
50
45
7.0
PtWn
–
–
19
20
17.7
PtWz
71
4.8
47
49
12.0

154

Dieck et al.

Fig. 1: The residuals of the UT1−UTC measurements from the USNO Intensive series with respect to the finals.all series
produced by the IERS Rapid Service / Prediction Center. The W-series baselines are shown with KkWz as a reference. No systematic
correction has been applied to the data in this diagram.

alternative frequency setups in different bands (Diecket al., 2019), the USNO Analysis Center is actively developing a collection of Python scripts and functions
called the General Repository of EOP Analysis Tools(GREAT).
The existing tools in GREAT revealed statisticallysignificant impacts on the UT1−UTC time series due
to motion of the MK-VLBA station. To see these
impacts, the software first calculates the residuals of
the time series with respect to one of three model
series: eopc04.62-now from the Paris Observatory,
latest midnight.eop from the NASA Jet Propulsion Lab, or, as is used in these analyses, finals.allfrom the USNO. Then an offset and a rate is calculatedby doing a least squares minimization fit. The resulting
first order polynomial is subtracted from the residuals,
resulting in a time series with a mean residual of zero.
This process is similar to the RS/PC characterizationof a baseline.
Examination of the UT1−UTC residuals at thisstage suggested there is a jump in early May 2018.
This event is coincident with the Kīlauea volcano
eruption on Hawai‘i and the associated 6.9 magnitude
earthquake, the epicenter of which is located ∼80 km

south east of MK-VLBA. The topographic deflation
around the island and up to ∼5 m of fault slip in
the southeasterly direction (Neal et al., 2019), which
occurred over the course of the eruption, could easily
cause a displacement in the position of the MK-VLBA
station.
To confirm that the jump is statistically significant,a tool was added to GREAT that performs a weighted
moving average over a time series by employing a
gaussian kernel density estimator with the kernel
bandwidth determined by leave-one-out cross validation (see Feigelson & Babu, 2019). An initial pass of
this smoother over the UT1−UTC residual time series
from November 14, 2015 (the resumption of MkPt
sessions after major maintenance at MK-VLBA) to thepresent revealed that the residuals not only jumped at
the time of the earthquake, but exhibit an unmodeledoscillation (with a primary period of ∼193 days)
throughout the baseline’s history. Further smoothing
was performed in two separate segments, divided
at the time of the earthquake (May 4, 2018, MJD
58242.940), which demonstrates that the discontinuity
in the MkPt UT1−UTC residuals is indeed statisticallysignificant (Figure 2).

MK-VLBA Intensives

155

Fig. 2: The residuals of the UT1−UTC measurements from the USNO intensive series with respect to the finals.all series fromthe IERS Rapid Service / Prediction Center. These series have systematic corrections applied so that the mean residual is zero prior to
the time of the earthquake, marked by the vertical dashed line. The MkPt VLBA Intensive series is in blue and the KkWz series is inorange. The light points are the residuals with errorbars for each session and the solid line is the gaussian kernel smoothed estimate
with the shaded region around the line denoting the 3-sigma confidence interval of the calculation of the estimate. The discontinuity
in the MkPt residual estimate demonstrates that the position of the MK-VLBA station did move, likely due to the Kīlauea eruption.

3 Future work: modeling an updated
a priori position for Mauna Kea withGPS
The ‘MKEA’ GPS station is co-located with the MKVLBA station at a separation of 87.8 m. We produced
position solutions for the station which confirm, independently of VLBI, that there was a displacement of
the Mauna Kea geodetic observation site down and to
the south east with a total magnitude of ∼15 mm (Figure 3).
The magnitude of the shift is consistent with the
VLBI measurement; at the earth rotation speed at
Mauna Kea (438 m/s), 15 mm ≈ 34 µs, within a factorof 2 of the magnitude of the jump in the UT1−UTC
VLBI residuals.
UT1−UTC estimates assume a fixed position;
therefore, the position displacement must be corrected
to utilize any Intensive observations made with MKVLBA, including both the W-series and the USNO
VLBA Intensives. To generate a new position history,

we will use the MKEA GPS position information to
extrapolate a position for each epoch of observation as
was done for the TSUKUB32 station by MacMillan
et al. (2013) following the 2011 earthquake in Japan.
Additionally, from the resulting position history of
the MK-VLBA station, we will develop parametricmodels of the station motion such as one of the
post-seismic deformation models now used in the
ITRF 2014 (Altamimi et al., 2016). These would thenbe used to predict the station’s motion and generatea priori positions for use with Intensives. Rather thandoing this once, the position history and model would
be regularly updated by including new GPS position
information.
We expect the corrections to eliminate the jump in
the residuals. Additionally, it appears upon visual inspection that oscillations in the north component of the
MKEA GPS station are correlated with the oscillations
seen in the MkPt baseline UT1−UTC residuals. The
updated positions may then also be able correct for theunexplained oscillations, if the connection is real.

156

Dieck et al.

Fig. 3: Relative GPS positions of the MKEA station in the North, East, and Up local tangent coordinates. These data start January
1, 2017 and are plotted with an arbitrary zero point. The individual measurements are showing in light blue circles with the solid
blue line denoting the gaussian kernel weighted moving average. The dot-dashed black line is a linear fit model to the positions both
before and after the earthquake, marked by the vertical dashed line.

Acknowledgements This work would not have been possible
without the work of Merri Sue Carter and Andrew Sargent of
the USNO for scheduling and correlating the W-series, respectively. Thanks also to Julien Frouard of the USNO for his assistance with the application of the kernel density estimator. The
authors acknowledge use of the Very Long Baseline Array under
the US Naval Observatory’s time allocation. This work supports
USNO’s ongoing research into the celestial reference frame andgeodesy. The VLBA is an instrument of the National Radio Astronomy Observatory which is a facility of the National Science
Foundation operated under cooperative agreement by Associated
Universities, Inc.

References
Altamimi Z, Rebischung P, Métivier L, et al. (2016)
ITRF2014.
JGR Solid Earth, 121, 6109–6131,
doi:10.1002/2016JB013098
Davis M, Carter M S, Dieck C (2019) The IERS Rapid Service/ Prediction Centre UT1−UTC Combined Solution: Present

and Future Contributions. In: R. Haas, S. Garcia-Espada,J. A. López Fernández (eds.): Proc. 24th EVGA Working
Meeting, 184–188
Dieck C, Johnson M, Fey A, et al. (2019) Navigating Across the
C-band –Experimental C-band Intensives with the VLBA.
In: K. L. Armstrong, K. D. Baver, D. Behrend (eds.):
IVS 2018 General Meeting Proceedings, NASA/CP-2019219039, 223–227
Feigelson E, Babu G (2012) Modern Statistical Methods for Astronomy.
Geiger N, Fey A, Dieck C, et al. (2019) Intensifying the Intensives with the VLBA. In: K. L. Armstrong, K. D. Baver,D. Behrend (eds.): IVS 2018 General Meeting Proceedings,
NASA/CP-2019-219039, 219–222
MacMillan D, Behrend D, Kurihara S (2013) Effects of the 2011
Tohoku Earthquake on VLBI Geodetic Measurements. In:
D. Behrend, K. D. Baver (eds.): IVS 2012 General Meeting
Proceedings, NASA/CP-2012-217504, 440–444
Neal C A, Brantley S R, Antolik L, et al. (2019) The 2018 rift
eruption and summit collapse of Kīlauea Volcano. Science
363, 6425, 367–374, doi:10.1126/science.aav7046

Initial Analysis of IVS-INT01 Schedule Degradation due to
Added Source Flux Catalog Latency
K. D. Baver, D. MacMillan, J. Gipson

Abstract Source flux catalogs provide source strength
information based on observations in IVS 24-hour sessions. It is important to have up-to-date fluxes because
if a source weakens without the catalog being updated
to reflect that, the source will be scheduled for too little
time, and its observations may fail. This is especiallyharmful for INT01 sessions, which have few observations. It currently takes at least two weeks to obtain andprocess a 24-hour session’s data, so each new source
flux catalog has an unavoidable minimum latency of
two weeks. But, because source flux catalogs are manually generated and manually retrieved by schedulers,
additional latency can be added by the time the catalogs
are used for scheduling. This often occurs in practice,with added latencies, at times, of a month or longer. We
look at the effect of added source flux catalog latency
on IVS-INT01 schedule degradation due to unrecognized source weakening.

Keywords Source flux · Latency · Intensive · UT1

1 Introduction
Source flux catalogs provide information about source
strength based on observations of the sources in IVS
24-hour sessions. It is important to have up-to-datefluxes because if a source weakens without the catalog being updated to recognize that, the source will be
Karen D. Baver · Daniel MacMillan · John Gipson
NVI, Inc., 7257D Hanover Parkway, Greenbelt Maryland,
20770, USA(Correspondence: karen.d.baver@nasa.gov)

scheduled for too little time, and its observations may
fail to achieve a viable SNR. This is a serious problem
for INT01 schedules given their small number of observations. Some latency is currently unavoidable; it takes
at least two weeks to obtain and process the data from
24-hour sessions. But added latency due to a delay ingenerating a catalog and/or using it for scheduling canbe controlled. We studied the effect of this added latency on IVS-INT01 scheduling and observing, focusing on degradation (observation failure and resulting
source failure and UT1 formal error increase) due tounrecognized source weakening.
We created artificial source flux catalogs spaced aweek apart using IVS 24-hour session data from mid2015 through early 2017. We then created 11 sets of 52
INT01-style base schedules spaced a week apart within
2016, where the schedules in each set were all createdwith a flux catalog of one of 11 added latencies: 1, 2,
3, 4, 5, 6, 8, 12, 16, 20, or 24 weeks. This allowed eachlatency to be tested with 52 one-hour schedules thatused sources from different slices of the sky that INT01
sessions observe throughout the year.
Table 1 shows the catalogs used for combinationsof schedule (session) dates and catalog latencies. We
chose the 52 Mondays in 2016 as the schedule dates,
and we assumed that each base schedule was made theprevious Friday with a catalog that added one to 24

Table 1: The out-of-date flux catalogs of 11 added latencies used

for schedules made for 52 days of the year (DOYs) in 2016.
schedule
added catalog latencies(session) dates one week two weeks ... 24 weeks
DOY 003 2015dec24 2015dec17 ... 2015jul16
DOY 010 2015dec31 2015dec24 ... 2015jul23
...
...
...
...
...
DOY 360 2016dec15 2016dec08 ... 2016jul07

157

158

weeks of latency beyond the unavoidable two week latency due to data processing. So, in line 1, the 11 Monday January 3 (day of year (DOY) 003) 2016 schedules were “created” on Friday December 31, 2015 withcatalogs that had at best one week of added latency(the 2015dec24 catalog, with data through the Thursday December 9, 2015 R4 session) and at worst 24
weeks of added latency (the 2015jul16 catalog, withdata through the Thursday July 1, 2015 R4 session).
We then ran two tests on the schedules. Test 1 (Section 2) evaluated the amount of theoretical scheduledegradation attributable to added source flux catalog
latency during scheduling. This test compared the baseschedules to schedules made from flux catalogs that
contained the best available (most up-to-date) information at the time of scheduling, as shown in Table 2, column 2. Test 2 (Section 3) evaluated how much degradation should actually occur if the base schedules wereobserved. This test used catalogs that modeled the realtime fluxes at the time of observing, as shown in Table
2, column 3. Because USNO currently alternates between scheduling INT01s with an 88-source source list
(the “MSS” list) and a 50-source list (the “BA 50” list),
we tested both schedule types.
Source flux catalog latency depends on how fast thesources’ fluxes are changing. Section 4 evaluates the
MSS sources’ behavior, focusing on source weakening.
We planned to work with catalogs that simulated
realistic catalogs. But, while operational catalogs use
averaged data from one to two months of 24-hour sessions, we accidentally only used data from a week ofsessions for each catalog. Using only one week of data
failed to smooth out isolated large flux changes that canoccur due to errors or anomalies such as using an atypical station network. We hope to redo the study later.
Meanwhile the current study provides initial insights.

Table 2: Catalogs used in testing. Column 1: 2016 “session

dates”. Column 2: corresponding test 1 catalogs (best available(most up-to-date) for scheduling). Column 3: corresponding test
2 catalogs (“real time” to model observing). The data in each catalog are two weeks old, so the 2016jan14 catalog, for example,
has data through December 30, 2015.
schedule
dates ofdates of(session) dates best available catalogs real time catalogs
DOY 0032015dec31
2016jan14
DOY 0102016jan07
2016jan21
...
...
...
DOY 360
2016dec22
2017jan05

Baver et al.

2 Scheduling degradation due tolatency
The first test evaluated scheduling degradation due toadded latency (how many observations would not havebeen scheduled if up-to-date source flux catalogs withno added latency had been used). This test is of theoretical interest only, because if up-to-date catalogs
had been used, the rejected observations would havebeen replaced by other observations. Using old fluxes
fails to recognize the weakening of some sources, andwith these sources being scheduled at the shorter durations appropriate to their original, higher strengths, thesources will achieve a lower, perhaps non-viable, SNR.
We ran the GSFC Sked scheduling program on eachbase schedule to reselect fluxes under its up-to-datecatalog, and we calculated the new SNR that resulted
for each observation from scheduling the observation’ssource for the observation’s original duration under
the source’s new flux values. We then discarded observations that failed to meet the minimum SNRs of
8 (X-band) and 10 (S-band) used in scheduling, because these observations would not have been scheduled under the up-to-date fluxes. We also determined
whether the observation loss eliminated any sourcesfrom the schedule. Finally, the unweighted UT1 formal error predicted from a schedule increases as thenumber of scheduled observations decreases. So we
compared the original and reduced schedules to determine the increase in the UT1 formal error attributable
to added catalog latency. Table 2, column 2, shows thecatalogs used for this test. The 24-hour data on which
each catalog was based were still two weeks out-ofdate, but this was the best available data at the time ofscheduling.
Figure 1 shows the average number of observations
for each added latency that would not have been scheduled under up-to-date flux catalogs. Averages are calculated over each latency’s 52 schedules. In the MSS
case, the number of unscheduled observations strictlyincreases with increasing latency, from 0.3 observations at one week of latency to 1.5 observations at 24
weeks of latency, and in the BA 50 case, it increases
from 0.1 observations at one week of latency to a maximum of 1.4 observations at 16 weeks of latency. We
used the Microsoft Excel “ttest” function to perform a
two-tailed t-test on pairs of sets of 52 schedules madewith catalogs of two different latencies, to see whether

INT01 Degradation from Added Latency

the differences between their counts of unscheduled
observations were statistically significant (which we
defined as having a t-test confidence level of at least
85 %). The decrease in the BA 50 counts after 16 weeksof latency is statistically insignificant, as are the MSS
differences starting at 16 weeks of latency.

Fig. 1: The average number of observations that would not havebeen scheduled under up-to-date fluxes vs. added source flux catalog latency in weeks: MSS (left) and BA 50 (right).

Figure 2 shows the average number of sources thatwould not have been scheduled under up-to-date flux
catalogs. The MSS count increases almost strictly withincreasing added latency, from 0.3 to 1.3 sources at 24
weeks of latency, although its differences become statistically insignificant at 16 weeks (1.0 sources). The
BA 50 count increases from 0.1 to a maximum of 0.8
at 16 weeks, although its differences become statistically insignificant at eight weeks (0.7 sources).

Fig. 2: The average number of sources that would not have beenscheduled under up-to-date fluxes vs. added source flux catalog
latency in weeks: MSS (left) and BA 50 (right).

Figure 3 shows the increase in the average unweighted UT1 formal errors due to added latency. The
MSS UT1 formal error increase generally grows from
0.2 µs to 0.5 µs, although its differences become almost
totally statistically insignificant at four weeks of added
latency. The BA 50 UT1 formal error increase grows
from 0.05 µs at one week of latency to a maximumof 0.5 µs at 12 weeks, although its differences become
statistically insignificant at three weeks.
Figure 4 shows the effect of added latency on the
UT1 formal error increases of individual schedules. As
latency (shown by 11 groups of five bars) increases,
the number of schedules with no change in the UT1

159

Fig. 3: The average increase in the UT1 formal error due to la-tency during scheduling vs. added source flux catalog latency inweeks: MSS (left) and BA 50 (right).

formal error (the left bar in each group) generally decreases, and the number of schedules with a formal
error increase gets larger. The “> 2.5 µs” category isof concern because each week of operational INT01
schedules comes from a single template, so each baseschedule represents five days of INT01 observing. The
largest values (> 3.5 µs) come from flux spikes, butsome individual DOYs’ schedules are vulnerable to latency. For example, starting at three weeks of latency,
the MSS DOY 122 schedule experiences an averageincrease of 2.6 µs. But in general, there is not a strict
growth in the UT1 formal error increase with added latency for individual DOYs.

Fig. 4: Number of schedules with a specific UT1 formal error increase range (µs) at different added source flux catalog latencies
for the MSS (left plot) and BA 50 (right plot) during scheduling.
Groups of five bars along the X-axis represent latencies that increase from left to right. In each group, individual bars represent
ranges of growing increase in the UT1 formal errors of individual schedules as the bars progress from left (no change) to right(change of > 2.5 µs) within the group.

On average, added source flux catalog latency does
not greatly affect scheduling. Within latencies ranging
from one to 24 weeks, the maximum average loss isonly 1.5 observations and 1.3 sources, and the maximum average UT1 formal error increase is only 0.5 µs.
Also, differences between average UT1 formal error
increases are not statistically significant after three orfour weeks of latency. The biggest danger is that someindividual DOYs’ schedules can experience large increases in their UT1 formal errors.

160

Baver et al.

3 Observing degradation due to latency
The actual effect of added source flux catalog latency
comes from the failure of scheduled observations during observing because they were scheduled for too little time to achieve a viable SNR when unrecognizedsource weakening occurred. This is of practical interest, because these failures are not detected until correlation, when it is too late to replace the failed observations. To evaluate this case, we used Sked to evaluate
the base schedules under the flux catalogs that modeled the fluxes at the time of observing. Better modeling would have involved the creation of new source
flux catalogs with a data span centered on the day theschedule would be “observed”. But for this first effort, we re-used the schedules from test 1, and for each(Monday) test schedule, we used data through the R4
on the preceding Thursday, which are contained in the
catalog dated two weeks later (e.g., for the January 3,
2016 schedules, the catalog dated 2016jan14). We used
Sked on each base schedule to reselect fluxes under the“real time” catalogs, calculated each observation’s new
SNR, and discarded observations that failed to meet theminimum SNR of 7 (X- and S-band) used in correlation. We compared the remaining observations to thebase schedules to evaluate the three metrics. Table 2,column 3, shows the flux catalogs used in this test.
Figure 5 (left) shows the average number of scheduled observations that would fail to be observed due
to added latency. There is little effect, and the number
fluctuates, presumably without statistical significance,
rather than growing with increasing latency. For eachschedule type, observation loss fluctuates between ∼0.08 and 0.19 observations, much less than the maximum of ∼ 1.5 in test 1. The average number of scheduled sources that would fail has an almost identical pattern, and its plot is not shown. Source loss fluctuates
between ∼ 0.07 and 0.15 sources, much less than the
MSS and BA 50 test 1 respective maxima of 1.3 and0.8 sources.
Figure 5 (right) shows the increase in the average
UT1 formal error that would occur due to added latency. Again, latency has only a small effect, and theincrease fluctuates between 0.02 µs and ∼ 0.12 µs instead of growing with increasing flux catalog latency.
This is again less than the 0.5 µs maximum in test 1.
Figure 6 shows the expected increase in the UT1formal error of individual schedules due to added la-

Fig. 5: Left: the average number of observations that would nothave been successfully observed vs. added source flux catalog
latency in weeks. Right: the average increase in the UT1 formal
error during observing vs. added latency in weeks.

tency. For both the MSS and the BA 50 cases, the number of schedules with a given UT1 formal error increase(e.g., no change, change < 0.5 µs etc.) fluctuates instead of changing with increasing latency. Also ∼ 45 of
the 52 schedules for each latency show no change to the
UT1 formal error, in contrast to test 1, where a lack ofchange was only seen in fewer than half of the schedules of approximately half of the latencies. So again
added latency has a smaller effect on degradation during observing than on degradation during scheduling.
If schedules are broken down by DOY, many DOYs’schedules show no change in the UT1 formal error for
any latency, and increasing latency does not generally
raise the UT1 formal error increase.

Fig. 6: Number of schedules with a particular range of UT1 formal error increase (µs) at different added source flux catalog latencies for the MSS (left) and BA 50 (right) during observing.

This test shows that added latency has little effect on observing degradation, and the effect does notincrease as latency increases. We think that latency
causes less observing than scheduling degradation because the correlation SNR limits are lower than thescheduling limits and exclude fewer observations.

4 Source behavior
Source flux catalog latency depends on how fast thesources’ fluxes are changing. Observation durations indirectly measure fluxes because a weaker source needs
more time to achieve a target SNR. So, to assess flux

INT01 Degradation from Added Latencychange rates, we used Sked to calculate the scheduled
durations for the 88 MSS sources at 26 DOYs, spaced
14 days apart, every five minutes for an hour starting at
18:30 UT, then averaged the durations over each hour.
We performed this evaluation using the 52 2016 artificial flux catalogs to assess the sources’ behavior overtime. We used an INT01-style schedule but allowed durations up to 600 seconds, to look at weaker sources.
The data included 41,560 duration differences (positive, negative or zero) over a week. 15.2 % were increases, showing that the source was weakening andcould be scheduled for too little time and fail to achievea viable SNR. The average duration increase over a
week was 40.6 seconds, with a standard deviation of
48.6 seconds and a maximum of 353.7 seconds (due tothe unsmoothed catalog fluxes). Table 3 columns 1 and2 show the distribution of the duration increases.
We evaluated how often unrecognized flux weakening should cause a scheduled source to become
too weak to be scheduled over the next week. INT01
sources are scheduled for 40 to 200 seconds, andTable 3 column 3 shows the durations of observations
that should become impossible to schedule given the
duration increase in column 1. Column 4 identifies
how many actual INT01 observations should be
affected. To determine this, we identified the durationsof 4,112 Kokee-Wettzell observations from the 2017
INT01 schedules, which all used the MSS source list.
Column 4 gives the distribution of these observations
within the column 3 ranges. So, using Table 3 line
1 as an example, 67.4 % of the increases should be
up to 40 seconds and should cause 45.8 % of INT01

Table 3: Duration increases over a week under test catalogs. Col-umn 1 shows ranges of duration increases in seconds, and column 2 shows the percentage of the increases that fell into theseranges in test schedules. Column 3 shows the duration ranges inseconds of observations that should become impossible to schedule given the duration increase in column 1. Column 4 shows thepercentage of 2017 INT01 Kokee-Wettzell observations that fall
into the ranges in column 3.
duration dpercentage of durations (secs) percentage ofincreaseincreases of observations occurrences
over a weekin testthat would failin INT01(secs)
schedules to be scheduled schedules
d <= 40
67.4 %
161 to 200
45.8 %
40 < d <= 80
18.4 %
121 to 200
55.1 %
80 < d <= 120
6.3 %81 to 200
69.5 %
120 < d <= 160
4.0 %41 to 200
90.0 %
160 < d3.9 %all observations 100.0 %161

observations (the ones with a duration of 161 to 200
seconds) to exceed the 200 second maximum duration
and become impossible to schedule. Because only
15.2 % of the duration differences over a week areincreases, column 2 should be multiplied by 15.2 %to see how often a case should occur overall. For
example, the line 1 case only occurs 67.4 x 15.2 %, or
7 %, of the time, and the line 4 case only occurs 0.6 %of the time. So the effect of latency is again small.

5 Conclusions and next steps
We generated artificial source flux catalogs to study theeffect of added source flux catalog latency on the degradation of MSS and BA50 schedules in scheduling andobserving. We accidentally included only a week, instead of a month or two, of data in each catalog, resulting in catalogs with unsmoothed flux spikes; however,this study offers initial insights.
Added latency degrades scheduling, and degradation generally increases with increasing latency. But
the average effect is small, and its impact on UT1
formal error increase is statistically insignificant after
three or four weeks. Latency causes even less degradation during observing, presumably because the correlation SNR limits are lower than the scheduling limits and exclude fewer observations. Degradation duringobserving fluctuates with presumed statistical insignificance instead of increasing with increasing latency.
Latency depends on how fast the sources’ fluxes
are changing. The average increase over a week in thelength of time needed to observe a source was only
40.6 seconds. Changes of up to 40 seconds would make
45.8 % of INT01 observations too weak to be scheduled due to unrecognized source weakening, but thesechanges should only occur 7 % of the time.
This initial work says that added source flux catalog latency causes little degradation, but this should
be confirmed using smoothed catalogs. Also, unrecognized weakening of sources is only one half of the effect of added latency. The other half is unrecognizedstrengthening, which counteracts degradation but cancause overly long observation durations which should
be reduced to avoid wasting time that could be used forother observations. We hope to perform a more comprehensive study of source flux catalog latency later.

HartRAO Site Tie Measurements: VLBI and Ground Survey
M. Nickola, A. de Witt, M. Schartner, R. C. Botha, C. S. Jacobs, J. Gruber, H. Krásná, W. L. Combrinck,
J. Böhm

Abstract A first short baseline VLBI experiment between the Hartebeesthoek Radio Astronomy Observatory’s (HartRAO) 26 m legacy and co-located 15 m radio telescopes has been conducted. The local automated site tie system at HartRAO is currently being
implemented and tested. The methodology of the two
approaches to local tie measurement, VLBI and groundsurvey, as well as results from the first short baseline
experiment are presented here.

Keywords VLBI · ITRF · Local tie · Short baseline

1 Introduction
If the Global Geodetic Observing System (GGOS) requirement of ± 1 mm accuracy (Beutler et al., 2009) is
to be met for global baselines, it must be possible to atleast reach this goal for the short baseline of ∼113 m
between the HartRAO 26 m legacy antenna and the
15 m co-located antenna (see Figure 1). Short baseline
experiments allow for discovering and investigating instrumental effects and antenna structure as the antennas
share a common location position, atmosphere, local
geophysics and clock. Short baseline experiments also
allow for determining the local tie between the telescopes. A first such short baseline experiment between
the HartRAO 26 m and 15 m antennas has been conducted.

Marisa Nickola · Aletha de Witt · Roelof C. Botha
Hartebeesthoek Radio Astronomy Observatory (HartRAO), PO
Box 443, Krugersdorp 1740, South Africa
Marisa Nickola · W. Ludwig Combrinck
University of Pretoria (UP), Private Bag X20, Hatfield 0028,
South Africa
Matthias Schartner · Jakob Gruber · Hana Krásná · Johannes
BöhmTechnische Universität Wien (TUW), Department of Geodesy
and Geoinformation, Gußhausstraße 27-29/E120, AT-1040 Vienna, Austria
Hana Krásná
Astronomical Institute of Czech Academy of Sciences (ASU),
Astronomical Institute ASCR, Fričova 298, 251 65 Ondřejov,
Czech Republic
Christopher S. Jacobs
California Institute of Technology, Jet Propulsion Laboratory/NASA, 4800 Oak Grove Drive, Pasadena, CA 91109,
United States of America(Correspondence: marisa@hartrao.ac.za)

Fig. 1: Short baseline of ∼113 m between the HartRAO 26 m

antenna (left) and the HartRAO 15 m antenna (right), with the
Leica MS50 Multistation in the foreground.

162

HartRAO Site Tie

The local automated site tie system at HartRAO iscurrently under test. Measurements to various on-site
GNSS reference stations, the NASA and Roscosmos
SLRs as well as to various reference piers will be performed on a regular basis towards fully automating thesystem. The HartRAO 26 m, 15 m and VGOS radio
telescopes will form part of these local tie measurements in due course. Measurements of VLBI reference
points, antenna axis offsets (AO) and station coordinates obtained by conventional survey with the total
station, will be used to complement the VLBI determined values.

2 Short baseline experiment
A first short baseline session, SBL500, was observedon the 11th of May 2018 with the HartRAO 26 m
and 15 m antennas. It consisted of a 4-hour session
conducted from 22:00 UT on the 11th of May until
02:00 UT on the 12th of May, well away from sunset and sunrise hours to ensure temperature stability.
It was not possible to run the antennas off the same
clock for this first short baseline experiment, yet. The
SBL500 session was scheduled with the Vienna VLBI
and Satellite software (VieVS Böhm et al., 2018) toobserve ICRF-2 defining sources at X-band at 2 Gbps,
covering the full range of azimuth (for east and northbaseline components), elevation (separating the vertical from the troposphere) and cable wrap.
The SBL500 session was subsequently correlated at the Vienna correlator with the Distributed
FX-architecture (DiFX) software VLBI correlation
package, using a spectral resolution of 0.2 MHz
and applying local oscillator (LO) frequency offsetsof 9999.9 Hz to HARTRAO. Fringe-fitting andpost-processing were also performed at the Vienna
correlator making use of the Haystack Observatory
Postprocessing System (HOPS) software package.
The SBL500 correlator output was made available
as vgosDB files. The SBL500 session was analysedwith VieVS. Earth Orientation Parameters (EOPs)
and coordinates of sources with the no-net-rotation(NNR) condition were not estimated. Thirty-eight
other parameters were estimated as follows:• troposphere zenith wet delay as piecewise linear
offsets (PLO) every 60 minutes with loose con-163
Table 1: Comparison of VieVS estimated values for baseline

components and length in SBL500 and corresponding values
measured during the 2014 local tie survey (Phogat et al., 2018).
Baseline 2014 Local tie survey VieVS estimation
component measurement (m)for SBL500 (m)X−48.0326 ± 0.0029 −48.0353 ± 0.0017
Y
102.2991 ± 0.0032 102.2991 ± 0.0021
Z−4.1238 ± 0.0073 −4.1286 ± 0.0014
Length
113.0895 ± 0.0187 113.0908 ± 0.0020

straints (6 parameters per station, 12 parameters intotal)• tropospheric gradients as PLO every 360 minuteswith loose constraints (3 parameters per station per
gradient, 12 parameters in total)• clock PLO every 60 minutes with loose constraints, one rate and one quadratic term per clock(6 parameters for PLO and 2 for rate and quadratic
term, 8 parameters in total)• station coordinates as one offset, datum definition
via no-net-rotation/no-net-translation (NNR/NNT)
condition (1 parameter per station per coordinate,
6 parameters in total)
Results for baseline components and baseline
length from the VieVS VLBI analysis of SBL500
and corresponding results from IGN measurements asdetermined during the February 2014 local co-location
survey (Muller and Poyard, 2015) are compared inTable 1. The results obtained from VLBI analysis
differ at the millimetre-level from the local tie survey
results.

3 Local tie ground survey
A local automated site tie system for continuous monitoring of vector ties is being implemented. The planned
measurement system is to consist of the one Leica
MS50 Multistation mounted on a permanent reference
pier (currently under test, see Figure 1) as well as anadditional Leica MS50 Multistation to be installed on
the roof of the Control room. Measurements are to bemade to the prisms installed on the antennas and reference network first. The planned reference network
is to consist of the on-site HRAO (IGS station), ESA,DLR and Russian GNSS to tie the measurement system in with GNSS observations to link it to the ITRF
(see Figure 2).

164

Nickola et al.

Fig. 2: VLBI local tie observing system – components of measurement and reference networks.

Fig. 3: Targets, consisting of a combination of Leica prisms andcustom-made adapters.

Fig. 4: Prism combination mounted at south end of 26 m polar

shaft acquired by the Leica MS50 Multistation.

It is intended to mount the targets on both the 26 m
and 15 m antennas on-axis where possible. Targets on
the 26 m antenna are to consist of prisms mounted oneach of the east and west ends of the declination shaft
as well as at the south end of the polar shaft (see figures 3, 4, and 5). The north end of the polar shaft
is obscured by the bearing housing, requiring the design of special adapters to mount prisms at this end.
On the 15 m antenna, it is possible to mount a prismat the west end of the elevation shaft. The east end of
the elevation shaft is obscured by the elevation cablewrap. Again, either special adapters will have to be designed to mount the prisms, or prisms will have to be
mounted off-axis at this end (see Figure 6). Similarly
for the 15 m’s azimuth axis, which is not accessible forthe placement of on-axis prisms. Any existing targets
on the antenna’s structure will also be employed. Targets will be measured by the two total stations, simultaneously, for various positions of the primary and secondary axes respectively.
For antennas with intersecting rotation axes, it isrelatively straightforward to determine the VLBI reference point. However, the rotation axes of the HartRAO
26 m polar-mount and 15 m azimuth-elevation (az-el)
mount do not intersect but an axis offset (AO) exists
for each of the antennas. For the 26 m antenna, the
VLBI reference point is represented by the intersectionof the fixed Hour Angle (HA) axis with the perpendicular plane containing the moving Declination (DEC)axis. For the 15 m antenna, the VLBI reference pointis represented by the intersection of the fixed azimuth
axis with the perpendicular plane containing the moving elevation axis.

HartRAO Site Tie

165

measurement, the intention is to, firstly, mount prisms
with their optical reference points coincident with therotation axis and then, secondly, mount prisms off-axis.
The antenna is subsequently moved about one of therotation axes with the other axis being held fixed ina specific position, for several different positions. Targets will then trace an arc in a circular plane normal tothe axis being measured. The axis intersects the planein the centre of the circle. The method suggested byCombrinck and Merry (1997) for finding the axis intersection and centre of the circle by making use of theintersection of co-planar lines, will be followed. Furthermore, comparing the results for on-axis and offaxis placement of prisms will allow for determining
whether the on-axis prism is a valid and accurate measurement point for future use.

4 Outlook
Fig. 5: HartRAO 26 m polar mount antenna – rotation axes andon-axis prism mounting points on Dec shaft (top and bottom arrows) and at south end of polar shaft (arrow in middle). The northend of the polar shaft is obscured by the bearing housing (arrowon right).

Fig. 6: HartRAO 15 m az-el mount – rotation axes and on-axis

prism mounting point at west end of elevation shaft (arrow onleft). The east end of the elevation shaft is obscured by the cablewrap (arrow on right).

For both the HartRAO 26 m and 15 m antennas,
indirect measurement of the VLBI reference point istherefore required. In order to accomplish this indirect

A local tie survey, including all geodetic techniques onsite, is currently in the planning stages. In addition to
the daily measurement of various targets in the measurement and reference network by the automated total station, it is envisaged that the local tie and shortbaseline sessions will be conducted on a monthly basis. During the short baseline sessions, the 26 m and15 m antennas will have to be run off the same clock.
Possible variations of the baseline length will be investigated and an error budget will be drawn up for the
short baseline ties. Once the VGOS telescope has been
furnished with receivers, it will be included in the shortbaseline sessions.

Acknowledgements Copyright 2019. All rights reserved.
HartRAO/SARAO is a facility of the National Research
Foundation (NRF), South Africa. The portions of this researchcarried out at the Jet Propulsion Laboratory, California Instituteof Technology were done under a contract with the National
Aeronautics and Space Administration. The authors acknowledge the IVS and all its components for providing VLBI data
(Nothnagel et al., 2017). The authors wish to thank Jonathan
Quick (HartRAO) for his contribution to the first HartRAO shortbaseline session.

166

References
Beutler G, Pearlman M, Plag H-P, et al. (2009) Towards GGOS
in 2020. In: H.-P. Plag, M. Pearlman (eds.) Global Geodetic
Observing System - Meeting the Requirements of a Global
Society on a Changing Planet in 2020. Chapter 10, 273–281,
doi:10.1007/978-3-642-02687-4 10.
Böhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and
Satellite Software (VieVS) for Geodesy and Astrometry.
PASP,130(986), doi:10.1088/1538-3873/aaa22b.
Combrinck W L, Merry C L (1997) Very long baseline interferometry antenna axis offset and intersection determina-

Nickola et al.

tion using GPS. J Geophys Res, 102(B11), 24741–24744,
doi:10.1029/97JB02081.
Muller J M, Poyard J C (2015) Hartebeesthoek local tie survey.
IGN report
Nothnagel A., Artz T., Behrend D., et al. (2017) International VLBI Service for Geodesy and Astrometry – Delivering high-quality products and embarking on observations of the next generation. J Geod, 91(7), 711–721,
doi:10.1007/s00190-016-0950-5
Phogat A, Kronschnabl G, Plötz C, et al. (2018) Short Baseline
Observations at Geodetic Observatory Wettzell. Data, 3(4),64, doi:10.3390/data3040064.

In-depth Analysis of Schedules Optimized for Certain VLBI
Experiments Using VieSched++
M. Schartner, J. Böhm, A. Müskens, A. Nothnagel, C. Plötz

Abstract Scheduling is an integral part of every VLBI
experiment and, at this stage, already determines thegeometric stability of the final solution. To increase thequality of the schedule, the TU Wien scheduling concept consists of two steps. The newly developed VLBI
scheduling software VieSched++ offers the possibility
to generate hundreds of different schedules for a single experiment automatically. Each of these schedules
is then simulated hundreds of times using the VieVS
VLBI module ending up with hundred thousands ofsimulations for a single experiment. The results areused to investigate the connection between scheduling
optimization criteria and scheduling parameters withgeodetic results gained during the analysis of simulations for the selection of the best suited schedule forthe session at hand. In this work, we are providing an
in-depth analysis of these correlations for the scheduleof the T2129 session. We will show the importance of
OHIGGINS for this network and highlight which optimization criteria play the biggest role in this session.

Keywords Scheduling · VieVS · VieSched++
Matthias Schartner · Johannes Böhm
TU Wien, Department of Geodesy and Geoinformation,
Gußhausstraße 27–29, AT-1040 Vienna, Austria
Arno Müskens · Axel Nothnagel
Rheinische Friedrich-Wilhelms-Universität Bonn, Institut fürGeodäsie und Geoinformation, Nußallee 17, DE-53113 Bonn,
Germany
Christian Plötz
Geodetic Observatory Wettzell, Federal Agency for Cartography
and Geodesy (BKG), Sackenrieder Straße 25, DE-93444 Bad
Kötzting, Germany(Correspondence: matthias.schartner@geo.tuwien.ac.at)

1 Introduction
The generation of a VLBI observing plan, the so-calledschedule can be seen as an advanced optimization
problem. So far, brute force algorithms are used togenerate schedules on a scan by scan basis (Gipson,
2010; Sun, 2013; Schartner and Böhm, 2019a). At
each step, all possible next scans are calculated,evaluated and compared to select the best one basedon optimization criteria. Unfortunately, developing
these optimization criteria is a serious challenge andsome of the criteria are competing against each otherlike the need for a good sky-coverage and the needto maximize the number of observations as discussed
in Gipson (2010) and Schartner and Böhm (2019a).
Therefore, understanding VLBI scheduling is criticalfor improving VLBI in general, since the schedule
directly determines which observations are available
during the analysis of the session.
During the analysis, typically the least squares
method is used where the correlations between estimated parameters can be derived directly (Nothnagel
et al., 2002). With the recent development of a new
VLBI scheduling software called VieSched++ (Schartner and Böhm, 2019a) and further developments inthe Vienna VLBI and Satellite Software (Böhm et al.,2018) it is now possible to look at correlations between scheduling parameters and estimated geodetic
parameters using Monte-Carlo simulations.
VieSched++ comes with a so-called multischeduling feature (Schartner and Böhm, 2019a,b),
where multiple schedules for one VLBI session canbe generated automatically. By simulating thesesessions multiple times, the scheduling statistics
are compared with repeatability values of estimatedgeodetic parameters as well as their formal errors.
167

168

This is demonstrated for a schedule of the official International VLBI Service for Geodesy and Astrometry(IVS) (Nothnagel et al., 2017), namely session T2129.
The goal of session T2129 is to provide highquality station coordinates which can be used to derive
terrestrial reference frames. In total, 15 VLBI stations
are participating in this session. From a schedulingpoint of view, this session is especially interesting,since it has many challenges: The network geometry is
far from optimal, with only two stations in the southernhemisphere, namely HART15M and OHIGGINS. Additionally, the sampling rate is very low with only 128
Mbit/s which is very problematic, since some antennas
have poor sensitivity such as OHIGGINS with system
equivalent flux densities (SEFD) of 10.000 Jansky(Jy) in X- and 18.000 Jy in S-band and VERAMZSWwith an SEFD of 13.160 Jy in S-band. Together withthe remote location of OHIGGINS in Antarctica,
generating an optimal schedule, where OHIGGINS isproperly included, is a serious challenge. This makes
it a perfect candidate to investigate the correlations
between scheduling statistics and estimated geodetic
parameters to understand how this challenging session
can be optimized from a scheduling point of view.

2 Method
Using the VieSched++ multi-scheduling feature, 500
schedules of session T2129 are generated. Each ofthese schedules follows a different scheduling logic
specified through their weight factors and through allowing subnetting or not (Schartner and Böhm, 2019a).
The weight factors directly determine the source selection and are therefore the most important factor one
can vary in order to optimize the schedule (Schartner
et al., 2017; Schartner and Böhm, 2019a,b). These sessions are then simulated 500 times each using VieVS.
Together, this leads to a total of 250.000 simulations
which can be analyzed. By combining the results of the
500 simulations per schedule, repeatability values canbe calculated as well as mean formal errors. Therefore,a series of scheduling values such as number of observations, as well as a series of repeatability and mean
formal error values are available and correlations canbe calculated between those.
The simulation is calculated including troposphericturbulences, clock drifts, and white noise (Pany et al.,Schartner et al.

2011), where the same simulation parameters are used
for all stations. The troposphere is simulated using
a turbulence simulator with Cn values of 1.8 · 10−7
m−1/3 (Nilsson et al., 2007) and scale height of 2 km,
the clock is simulated using random walk and integrated random walk with an Allan standard deviationof 1 · 10−14 after 50 minutes (Herring et al., 1990), andadditionally 30 ps white noise is added to the observations.

3 Results
Figure 1 shows the correlation matrix between thescheduling parameters gained from 500 different
schedules generated for session T2129. The first six
rows and columns list general scheduling statistics,
like the number of scans, the number of observations
and the number of observed sources. The numberof scans is further divided into scans scheduled with(“subnetting scans”) and without (“single sourcescans”) subnetting and scans scheduled during fillinmode. Subnetting is a technique, where the software
decides to split the network into two pieces andtherefore is considering two scans simultaneously
during the scheduling algorithm (Petrov et al., 2009).
Fillin-mode is a concept which is used to reduce
station idle time. During the wait time for slower
slewing antennas, it is often possible to squeeze inanother scan using a reduced antenna network, whichis called fillin-mode (Gipson, 2010). VieSched++ uses
a recursive scan selection to implement fillin-modescans, see Schartner and Böhm (2019a,b).
Followed by the general scheduling statistics, thenumber of scans and observations are listed for eachstation. The last five rows and columns are the multischeduling parameters, which were varied to create theschedules. Among those are four weight factors and aboolean type parameter which shows whether subnetting was allowed during the creation of the schedule ornot.
By focusing on the top left corner in Figure 1 where
the correlations between the general scheduling statistics are visualized one can see that there is obviously
a strong negative correlation between the number ofscans scheduled with and without subnetting but alsoa negative correlation between the number of fillin-Analysis of VieSched++ Schedules

169

Fig. 1: Correlations between scheduling statistics.

mode scans and subnetting scans. While the first negative correlation can simply be explained by the definition that the sum of the scheduled subnetting scans andthe scans scheduled without considering subnetting is
the total number of scans. The second negative correlation is due to the better consideration of all stations
when using subnetting which results in fewer fillinmode scans. Interestingly, a high number of subnettingscans also results in a lower total number of observations, which also can be explained by the splitting of
the full network into two smaller ones during subnetting. Additionally, there is a small negative correlation
between the number of scheduled sources and the total
number of observations.
When looking at the correlations between the general scheduling statistics and the number of observations per station, some interesting characteristics canbe seen: All but two antennas show a strong positive
correlation between the total number of observations
and the number of observations per antenna. The only
exception is HART15M, showing only a low positive
correlation and OHIGGINS which is negatively corre-

lated. This means, that a high number of observations
with OHIGGINS results in a lower total number of observations in this schedule, which can be explained by
the high cost of the inclusion of OHIGGINS into theschedule due to its remote location and very low sensitivity. Additionally, it can be seen that OHIGGINS getsthe highest number of observations when subnetting isused extensively which can be explained through its
remote location. This can further be confirmed whenlooking at the cross-correlations between the numberof observations of individual stations. While the number of observations of almost all stations is strongly
positively correlated, the number of observations of
HART15M is almost not correlated with other stations,and the number of observations with OHIGGINS isnegatively correlated with the number of observations
with all other stations except HART15M.
While the previously discussed characteristics arenecessary to understand VLBI scheduling, the mostinteresting question is how to generate a good schedule. This can be illustrated when looking at the correlations between the multi-scheduling parameters with

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Schartner et al.

Fig. 2: Correlations between scheduling statistics and accuracies of estimated geodetic parameters.

the other quantities since the multi-scheduling parameters are the only input parameters which are changed
to derive the different schedules. When looking at themulti-scheduling parameters, the enabling of subnetting clearly has the biggest effect on the result. It isstrongly negatively correlated with the number of observations of all antennas except for OHIGGINS whereit shows a positive correlation. Similar behavior can beseen for the weight factor which aims to average out
the number of observations over each baseline (“weightavg. baselines”). This makes sense since OHIGGINS
has the lowest number of observations thus leading
to baselines with a low number of observations. The
baselines then get a high weight during the scheduling logic resulting in an on average higher number ofobservations with OHIGGINS when the average baseline weight factor is given a high value, see Schartner
and Böhm (2019a). It can also be verified that giving
high weight to optimize the sky coverage, the numberof observations is lowered due to the longer slew times.

This effect can be countered by increasing the weightof the duration of a scan as well as the number of observations per scan, which results in more scans withmore participating stations and, consequently, a higher
number of total observations. As already discussed by
Gipson (2010) and Schartner and Böhm (2019a) finding a sweet-spot between the optimization of the skycoverage and the number of observations is one of themain challenges in geodetic VLBI scheduling.
Figure 2 depicts the correlation between scheduling
statistics and geodetic parameters derived from simulations. The first half of the columns shows repeatability values derived from the 500 simulations per schedule, while the second half shows the mean formal error
gained from the least squares adjustment. When looking at the correlations between the general scheduling
statistics, in the first few rows with the geodetic parameters, it is evident that many subnetting scans significantly lower the formal errors and the repeatabili-

Analysis of VieSched++ Schedules

ties due to their negative correlation resulting in better
results. Surprisingly, there is a positive correlation between the total number of observations and especiallythe formal errors, meaning that a higher number of observations results in poorer geodetic results. While thismight seem wrong, it makes perfect sense in this case:First, a high total number of observations results in apoorer sky-coverage since the slew times are kept low
and a good sky-coverage is necessary to estimate tropospheric time delays which are among the biggest error
sources in geodetic VLBI (Schuh and Böhm, 2013).
Additionally, it can be seen that especially observations with OHIGGINS show the biggest positive effecton the geodetic results and as already discussed previously, a high number of observations with OHIGGINS
results in a low total number of observations. As already discussed: While a high number of observations
is usually desirable, one has to find the sweet-spot between a high number of observations and a good skycoverage.
Considering the multi-scheduling parameters
shown in the last rows, it is evident that especiallythe allowance of subnetting has the most significant
positive effect on the geodetic results, followed by agood sky coverage and a short duration of individual
scans.

4 Conclusions and outlook
VieSched++ is using a multi-scheduling feature to create not only a single schedule for a session but multiple ones simultaneously. Based on Monte-Carlo simulations these schedules can be compared based on
geodetic results to select the best schedule. As a byproduct, correlations between scheduling statistics andestimated geodetic parameter accuracies can be calculated as shown here for session T2129. For these sessions, especially the proper inclusion of OHIGGINS
plays an important role to optimize the schedule. Theinteraction between scheduling optimization criteria
like improvement in the sky-coverage and maximizing
the number of observations as well as scheduling features like subnetting are discussed.
While these results are only valid for session T2129
with its unique network geometry and challenges, thegeneration of the schedules and simulations, as wellas the calculation of the correlation parameters, are171

fully automated in VieSched++ and VieVS to be able
to replicate this study for all schedules generated with
VieSched++.

ReferencesBöhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry. PASP,
130, 044503, doi:10.1088/1538-3873/aaa22b
Gipson J (2010) An Introduction to Sked. IVS 2010 General
Meeting Proceedings, 77–84
Herring T, Davis J, Shapiro I (1990) Geodesy by radio interferometry: The application of Kalman Filtering to the analysis
of very long baseline interferometry data. J Geophys Res,95, 12561–12581, doi:10.1029/JB095iB08p12561
Nilsson T, Haas R, Elgered G (2007) Simulations of atmospheric path delays using turbulence models. Proc. 18th
EVGA Working Meeting, 175–180
Nothnagel A, Vennebusch M, Campbell J (2002) On correlations
between parameters in geodetic VLBI data analysis. IVS
2002 General Meeting Proceedings.
Nothnagel A, Artz T, Behrend D, et al. (2017) International
VLBI Service for Geodesy and Astrometry. J Geod, 91,
711–721, doi:10.1007/s00190-016-0950-5
Pany A, Böhm J, MacMillan D, et al. (2011) Monte Carlo simulations of the impact of troposphere, clock and measurement
errors on the repeatability of VLBI positions. J Geod, 85,
39–50, doi:10.1007/s00190-010-0415-1
Petrov L, Gordon D, Gipson J, et al. (2009) Precise geodesy with
the Very Long Baseline Array. J Geod, 83, 859–876
Schartner M, Böhm J, Mayer D, et al. (2017) Recent Developments in Scheduling with VieVS. In: R. Haas, G. Elgered(eds.): Proc. 23rd EVGA Working Meeting, 113–116
Schartner M, Böhm J (2019a) VieSched++: A New VLBI
Scheduling Software for Geodesy and Astrometry. PASP,
131, 084501, doi:10.1088/1538-3873/ab1820
Schartner M, Böhm J (2019b) VieSched++: A new Scheduling Tool in VieVS. In: K. L. Armstrong, K. D. Baver,D. Behrend (eds.): IVS 2018 General Meeting Proceedings,
NASA/CP-2019-219039, 71–75
Schuh H, Böhm J (2013) Very Long Baseline Interferometryfor Geodesy and Astrometry. Berlin, Heidelberg: Springer,
339–376, doi:10.1007/978-3-642-28000-9 7
Sun J (2013) VLBI scheduling strategies with respect to
VLBI2010. Geowissenschaftliche Mitteilungen, 92

A Modified Approach for Process-Integrated Reference Point
Determination
M. Lösler, C. Eschelbach, S. Riepl, T. Schüler

Abstract The Global Geodetic Observing System (GGOS) calls for continues and automateddetermination of the geometric reference points ofspace-geodetic techniques such as DORIS, GNSS,SLR and VLBI. Whereas the reference points of
DORIS beacons and GNSS antennas can simply bemeasured by observing well-defined reference markers, the determination of SLR and VLBI reference
points are a metrological challenge, because thesereference points are inaccessible and non-materialized.
Indirect methods are needed to estimate the reference
points in a rigorous way, which fulfil the requirements
on an automated and continues reference point determination of the Global Geodetic Observing System. In
this investigation, a modified approach for reference
point determination of SLR and VLBI telescopes ispresented. The results of the new approach are compared to proven reference point models. The numericaldeviations of the estimated reference point coordinates
and the axis-offset are 50 µm and demonstrate theequivalence of the new approach.

Keywords Reference Point Determination · SLR ·VLBI · Laser Tracker · Least-Squares Adjustment ·In-Process Metrology · GGOS · VGOS
Michael Lösler · Cornelia Eschelbach
Frankfurt University of Applied Sciences, Laboratory for Industrial Metrology, Nibelungenplatz 1, DE-60318 Frankfurt am
Main, Germany
Stefan Riepl · Torben Schüler
Federal Agency for Cartography and Geodesy, Geodetic Observatory Wettzell, Sackenrieder Str. 25, DE-93444 Bad Kötzting,
Germany(Correspondence: michael.loesler@fb1.fra-uas.de)

1 Reference point determination model
Reference point determination is a challenging metrological task in the framework of reverse engineering.
Here, the telescope is analyzed and virtually deconstructed into its geometrical basic elements to reveal its
desired design parameters, e.g. the reference point or
the axis-offset. Such a model parametrizes the transformation of a telescope coordinate frame onto an Earthfixed global geodetic reference frame (e.g. Lösler andHennes, 2008; Kallio and Poutanen, 2012).
Based on observed trajectories of mounted targets,telescope specific parameters are estimable by
P j,k = PIRP + . . .
+ Rx,β Ry,α RTz,κk Ry,γ EAO + Rx,ωk p j .

(1)Here, matrix R denotes a basic rotation sequence thatrotates around the axis and angle given in sub-index.
TThe axis-offset is given by EAO = 0 eAO 0 . The angle γ compensates for the non-orthogonality between
the primary and the secondary axis. The tilt of the primary axis w.r.t. to the global frame is parameterised by
the correction angles α and β. The position p j referredto the telescope frame and rotated by κk and ωk aroundthe primary and secondary axis, respectively, corresponds to the position P j,k in the global frame. The geometrical reference point of the telescope is PIRP , which
is often denoted as invariant reference point (IRP).
Figure 1 depicts the model parameters of the transformation model and the physical connection of the
global geodetic reference frame (blue) and the telescope fixed coordinate system (green). The trajectoryof the j-th marker P j is pictured in several telescopeorientations.
172

Process-Integrated Reference Point Determination

173

𝑍

Primary axis = 𝑧𝑌𝜅𝐏𝑗,𝑘−2
𝐏𝑗,𝑘−1

𝑦

𝜔𝑘−1

𝑒AO

𝜔𝑘−2

𝐏IRP
𝐏𝑗,𝑘

𝜔𝑘

𝛾

𝜔
Secondary axis𝑥𝑋of the new IRP II approach (Eq. 1) is the exclusionof the datum definitions of the angle encoders. The
IRP II approach defines κk and ωk as additional unknown but fixed model parameters. The observations
are only the observed marker positions P j,k . Each observed P j,k provides three functional equations, which
can be expressed as functions of the unknown parameters. Thus, ordinary least-squares techniques are sufficient to estimate the parameters (e.g. Mikhail, 1976,
Ch. 5). However, the normal equation becomes singular because the parameters of the right hand side of
Eq. 1 are unknowns, i.e., the positions p j defined in thetelescope frame as well as the parameters to transformp j to the global geodetic frame are unknown. To solve
the defect of the normal equation system, a modified
observation and analysis strategy is needed.

Fig. 1: Resulting trajectory of the mounted marker P j observedin several telescope orientations w.r.t. the global geodetic frame
and the telescope frame (Lösler et al., 2018a).

Eq. 1 is similar to the mathematical model, derived
by Lösler (2008) and refined by Kallio and Poutanen(2012). Hereafter, the former approach is referred toas IRP I approach. The IRP I approach needs the observed angle encoder values of the telescope while thespecific marker was registered by the terrestrial measurement system (e.g. Lösler and Hennes, 2008). Thus,a strict synchronisation of both, the measurement system and the telescope, is essential. As shown by Lösler
et al. (2016), the uncertainty of the synchronisation corresponds to a position uncertainty of about 100 µm m−1(worst-case) and, therefore, becomes a significant component of the total uncertainty. The synchronisation
can be optimised by e.g. providing a stable trigger signal or a direct-reading of the telescope encoders. However, a better synchronisation only transfers the problem to a higher level of uncertainty but does not solve
the original synchronisation problem.

2 IRP II approach
The goal of the new IRP II approach is to remove thedependence between the terrestrial measurement system and the telescope and, thus, to fully eliminate synchronisation errors. Hereafter, this new approach is referred to as IRP II approach. The inherent difference

1. At least two markers must be mounted at the telescope to be sensitive for changing in telescope rotations.
2. These two markers must be observed at the sametime k in at least two different telescope orientations, e.g. κk , ωk and κk+m , ωk+m , with m > 0.
3. If more than two markers are mounted, subsets ofat least two markers have to be selected and step 2
is repeated until the necessary topological information between all mounded markers is defined.
4. A no-net-rotation (NNR) constrain has to be introduced to solve the remaining datum defect of thesecondary angle of the telescope.
The first three conditions are related to the observation process and can easily be done at the beginning
or in the end of the normal operation procedures of
the telescope or during maintenance intervals, if polarmeasurement instruments are used. A promising alternative to polar measurement instruments is the usageof mounted tracking GNSS antennas (e.g. Kallio andPoutanen, 2012; Ning et al., 2015). The forth condition concerns the adjustment process. Secondary angle based NNR constrains as well as coordinate based
NNR constrains can be formulated, to solve the remaining rotation defect of the normal equations, andare discussed in detail by Lösler et al. (2018a, 2019). It
should be noted that the NNR constrain does not affectthe reference point position or the axis-offset but theestimated positions p j as well as the angles κk and ωk .

174

Lösler et al.

0°

3 Model verification at SOS-W

30

330°

The Geodetic Observatory Wettzell (GOW) is a corestation in the framework of the GGOS (cf. Plag andPearlman, 2009, Ch. 2.8.1) and hosts instruments offour independent space-geodetic techniques at one site,
i.e. eight GNSS antennas, one DORIS beacon, three
VLBI radio telescopes and two SLR laser telescopes(e.g. Mähler et al., 2018). The observatory is cooperatively operated by the German Federal Agency for Cartography and Geodesy together with the Technical University of Munich.
For model verification that bases on real measurements, controlled environment and high-precision
measurement instruments are needed, to achieve a
better signal-noise-resolution, i.e., to separate modelrelated and measurement-related deviations. For thatreason, the radome enclosed SLR laser telescope, theSatellite Observing System Wettzell (SOS-W), waschosen (Riepl et al., 2005). The protection radomeoffers a stable and controllable meteorological environment where e.g. the temperature will not falsify
the measurements. The local terrestrial measurements
were carried out by Hexagon’s high-precision mobile
Laser Tracker AT401. The measurement uncertainties
of the instrument are specified by the manufacturer
as 15 µm + 6 µm m−1 . The protecting radome limits
the measurement distance between the SOS-W andthe laser tracker to <2.5 m. For that reason, the SLR
telescope was equipped with four so-called Cat-Eyereflector (CER) at the turnable alidade. The CER
provides a wide laser acceptance angle of ±60°.

300°

180°
150°
120°
90°
60°
30°

60°

90°

270°

Super Cat-Eye (±75°)120°240° Cat-Eye (±60°)
Corner-Cube (±30°)

150°

210°
180°

Fig. 2: Accepting range w.r.t. the telescope angles κk and ωkfor common Corner-Cube reflector (±30°) as well as for the twowide laser acceptance angle type reflectors: Cat-Eye (±60°) andSuper Cat-Eye (±75°).

metrology was realised as suggested by GGOS (cf.
Plag and Pearlman, 2009, Ch. 9.3.8).
For the first configuration the CER were aligned atright angles to the line of sight of the SOS-W, while
for the second configuration the same reflectors werealigned in parallel to the line of sight. Figure 3 depicts
the prepared telescope of the second configuration as
well as the automated measuring AT4011 . Five welldistributed instrument stations around the SOS-W were1 https://youtu.be/Mdwt1VsWb68

For a single instrument station Figure 2 depicts theobservable positions of a CER, which is mounted at
the SOS-W. For comparison, the range of a common
Corner-Cube reflector (CCR) and a Super Cat-Eye reflector (SCER) are also shown, that provide an accepting angle of ±30° and ±75°, respectively. For a complete hemispherical coverage, at least three instrument
stations are needed, if CER or SCER are used. Furthermore, 14 CCR were used to combine the measurementsof the instrument stations w.r.t. to the global geodetic
reference frame.

In spring 2018, five fully automated reference
point determinations were carried out at SOS-W,
using different reflector configurations. The software
package HEIMDALL was employed for controllingand scheduling the laser tracker. Thus, automatedFig. 3: Automated ILRS reference point determination of theSatellite Observing System Wettzell, using the high-precisionmobile laser tracker AT401.

Process-Integrated Reference Point Determination

selected, so that at least six CCR of the global geodetic
reference system were observable from a single instrument station, cf. Fig 4.
The registered observations to more than 2.200
marker position of the five measurement campaigns were analysed together by a so-called
6-DOF least-squares network adjustment, using
Java·Applied·Geodesy·3D2 software package (e.g.
Lösler et al., 2018b). The adjusted coordinates aswell as the fully populated dispersion matrix of the
network adjustment process were introduced to thereference point determination model. Due to the lackof reference values for SOS-W, two approved models
were used for deriving the reference point as well. The
first approved model is the IRP I approach, which isapplied for many years and not only at GOW (e.g.
Kallio and Poutanen, 2012; Ning et al., 2015; Mähler
et al., 2018). The second approved approach is thesphere fit that is usually used for reference point
determinations of the ILRS laser telescopes at Wettzell(cf. Klügel et al., 2012; Riepl et al., 2019). The modelof the sphere offers the smallest number of unknown
2 https://applied-geodesy.org

175

parameters but presupposes an intersection of both
telescope axes.
Table 1 summarises the obtained results of the reference point and the axis-offset derived by different
approaches. The model deviations are negligible w.r.t.
the uncertainties of 50 µm. In particular, the estimatedaxis-offset is insignificant and, thus, results in a highconformity of the estimated reference point between
the sphere fit and the IRP I and IRP II approaches.
Nevertheless, telescopes with axis-offsets exist and areincompatible to the sphere model. An existing but unknown axis-offset causes, when unaccounted for, systematic errors in Earth orientation parameters and biases the intra-technique derived topocentric verticalcomponent of the reference point (e.g. Combrinck andMerry, 1997; Nilsson et al., 2015).
Table 1: Comparison of estimated reference point position PIRP
derived by IRP I, IRP II and sphere approaches. The axis-offset
eAO is only parametrizable by IRP I and IRP II approaches. The
variations of the estimated parameters are 50 µm for the coordinate components and the axis-offset.
Approach XIRP in m YIRP in m ZIRP in m eAO in mm
IRP I
100.16246 197.69374 50.01237 −0.03
IRP II
100.16246 197.69376 50.01234 −0.02
Sphere100.16247 197.69375 50.01234–

4 Conclusions

Fig. 4: Configuration of the complete realised network aroundthe SOS-W. The more than 2.200 observed marker position at
the SOS-W are symbolised by magenta dots as well as related
confidence intervals (1σ, 1500:1). Points of the global geodetic
reference frame are depicted as blue hexagons. Realised metrological observations from several instrument stations are plottedin grey coloured dashed lines. The 6-DOF least-squares network
adjustment was carried out using Java·Applied·Geodesy·3D software package.

A modified approach for ILRS as well as IVS reference point determination was presented. The new approach is similar to the former model derived by Lösler
and Hennes (2008) and refined by Kallio and Poutanen (2012) but overcomes the necessary synchronisation between the terrestrial instrument and the telescope. The GGOS strives on an automated and continues reference point determination of space-geodetic
techniques (cf. Plag and Pearlman, 2009, Ch. 9.3.8).
The new approach allows for an in-process metrological determination of the reference point of such
space-geodetic techniques and fulfils the GGOS requirements.
Using the high-precision mobile laser tracker
AT401, more than 2.200 marker positions wereobserved at the Satellite Observing System Wettzell.
Based on the adjusted marker positions and the related

176

fully populated dispersion matrix, the ILRS reference
point was derived, applying the new IRP II approach.
The parameter uncertainties are about 50 µm. Basedon the same data set, the ILRS reference point is as
well derived by two approved models. The variationsof the estimated parameters between all evaluated approaches are 50 µm for the coordinate components
and for the axis-offset. Thus, the IRP II approachyields comparable results. The estimated axis-offsetof the SOS-W is insignificant w.r.t. to the derived
uncertainties and, thus, the sphere model is applicable.
Nevertheless, telescopes with axis-offsets exist andneed a more specific model like the presented IRP
approaches.
Acknowledgements We thank Swetlana Mähler for technicalsupport and providing the adapters of the Cat-Eye reflectors,
which enabled a free choice of positioning at the telescope structure. This research project is part of the JRP 18SIB01 ”Largescale dimensional measurements for geodesy” (GeoMetre) andhas received funding from the EMPIR programme co-financedby the Participating States and from the European Union’s Horizon 2020 research and innovation programme.

References
Combrinck W L, Merry C L (1997) Very Long Baseline Interferometry Antenna Axis Offset and Intersection Determination using GPS. J Geophys Res, 102(B11), 24741–24744,
doi:10.1029/97JB02081
Kallio U, Poutanen M (2012) Can We Really Promise a mmAccuracy for the Local Ties on a Geo-VLBI Antenna. In:
Kenyon S, Pacino M, Marti U (eds.): Geodesy for Planet
Earth, Springer, 136, 35–42, doi:10.1007/978-3-642-2033815
Lösler M, Hennes M (2008) An Innovative Mathematical Solution for a Time-Efficient IVS Reference Point Determination. In: Proc. joint Symposia: 13th FIG Symposium on
Deformation Measurement and Analysis and 4th IAG Symposium on Geodesy for Geotechnical and Structural Engineering – Measuring the Changes
Lösler M (2008) Reference Point Determination with a new
Mathematical Model at the 20 m VLBI Radio Telescope inWettzell. JAG, 2(4), 233–238, doi:10.1515/JAG.2008.026

Lösler et al.

Lösler M, Haas R, Eschelbach C (2016) Terrestrial Monitoringof a Radio Telescope Reference Point Using Comprehensive Uncertainty Budgeting – Investigations during CONT14
at the Onsala Space Observatory. J Geod, 90(5), 467–486,
doi:10.1007/s00190-016-0887-8
Lösler M, Eschelbach C, Riepl S (2018) A Modified Approachfor Automated Reference Point Determination of SLR and
VLBI Telescopes. tm – Technisches Messen, 85(10), 616–
626, doi:10.1515/teme-2018-0053
Lösler M, Eschelbach C, Jarecki F (2018)
Auswerteund Analysestrategie für automatisierte untertägige
Überwachungsmessungen.
In: J. Benndorf (ed.): 19.
Geokinematischer Tag. TU Freiberg, 64–78
Lösler M, Eschelbach C, Riepl S, et al. (2019) Zur Bestimmungdes ILRS-Referenzpunktes am Satellite Observing System
Wettzell. In: Luhmann T, Schumacher C (eds.): Photogrammetrie - Laserscanning - Optische 3D-Messtechnik: Beiträge
der 18. Oldenburger 3D-Tage 2019, Wichmann, 162–175
Klügel T, Mähler S, Schade C (2012) Ground Survey and Local
Ties at the Geodetic Observatory. In: Proc. 17th International Workshop on Laser Ranging, Mitt. BKG, 48, Frankfurt, 127–131
Mähler S, Klügel T, Lösler M, et al. (2018) Permanent Reference Point Monitoring of the TWIN Radio Telescopes at theGeodetic Observatory Wettzell. avn – Allgemeine Vermessungsnachrichten, 125(7), 210–219
Mikhail EM (1976) Observations and Least Squares. Univerity
Press of America, Lanham
Nilsson T, Mora-Diaz J A, Raposo-Pulido V, et al. (2015) Antenna Axis Offsets and their Impact on VLBI derived Reference Frames. In: T. van Dam (ed.): REFAG 2014 – Proceedings of the IAG Commission 1 Symposium, 146, Springer,
53–58, doi:10.1007/1345 2015 126
Ning T, Haas R, Elgered G (2015) Determination of the local
tie vector between the VLBI and GNSS reference points at
Onsala using GPS measurements. J Geod, 89(7), 711–723,
doi:10.1007/s00190-015-0809-1
Plag H-P, Pearlman M (2009) Global Geodetic Observing System – Meeting the Requirements of a Global Society on a
Changing Planet in 2020. Springer, Berlin, doi:10.1007/9783-642-02687-4
Riepl S, Schlüter W, Dassing R, et al. (2005) The SOS-W –A two colour kilohertz SLR system. In: Proc. 14th International Laser Ranging Workshop, Ministerio De Defensa,
Real Instituto y Observatorio de la Armada (ROA)
Riepl S, Müller H, Mähler S, et al. (2019) Operating two SLR
systems at the Geodetic Observatory Wettzell: from local
survey to space ties. J Geod, 1–9, doi:10.1007/s00190-01901243-z

2018 IVS Network Performance
M. Bérubé, E. Himwich

Abstract In 2018, the IVS scheduled over 193 VLBI
sessions for geodesy and astrometry. These 24-hoursessions involved more than 39 VLBI antennas operating in networks of 4 to 20 stations. As of today, 154sessions have been correlated and analysed. These sessions required 1455 station-days and 494823 recordedscans. In 2018, over 85 % of data recorded at the VLBI
stations made it through the correlators. Understanding the reasons for this data loss is critical for maintaining a high performance IVS network. This reportwill be presenting the main causes of missing data forthe 2018 IVS Network with emphasis on stations having participated in 50 sessions or more. The results arealso compared with previous years. The effect of RFI
on stations will also be presented.

the correlators and over 68 % were used by analysts.
T his is consistent with previous years. Understanding
the reasons for data loss is critical in maintaining a highperformance IVS network.

2 2018 S/X observing network
The 2018 S/X observing network consists of 50 stations. This includes the 37 IVS Network Stations as official member components of the IVS as well as several
cooperating sites that contribute to the IVS observing
program, in particular the 10 stations of the VLBA and3 NASA DSN stations as shown in Figure 1.

Keywords VLBI · IVS

1 Introduction
In 2018, the International VLBI Service for Geodesy
and Astrometry (IVS) scheduled over 193 VLBI sessions for geodesy and astronomy. These 24-hour sessions involved 50 VLBI antenna operating in networksof 4 to 20 stations. As of today, 154 sessions have beencorrelated and analyzed. These sessions required 1455
stations-days and 494823 recorded scans. In 2018, over
85 % of data recorded at VLBI stations made it throughMario Bérubé · Ed Himwich
NVI, Inc., 7275D Hanover Parkway, Greenbelt, Maryland,
20770, USA(Correspondence: mario.berube@nasa.gov)

Fig. 1: Distribution plot of the VLBI stations that contributed to

the 2018 IVS Master Schedule.

3 Network performance
The network performance is based on correlator andanalysis reports from all 24-hours experiments corre177

178

lated as of February 28, 2019. Experiments correlated
at VLBA were also included since available reports
provided relevant information on reasons for data loss.
The average number of stations per session is 9.4. Figure 2 shows the number of sessions that have been correlated for each station. Some stations have observed
more than shown since 39 additional sessions are notcorrelated yet. In 2018, the 50 stations delivered an average of 85 % of their data. To better understand thisglobal performance, the network has been analyzed bygroups based on the station usage.

Bérubé and Himwich

Fig. 3: Historical data yield since 2000.

Fig. 4: Percentage of data loss for each sub-systems in 2018
Fig. 2: Number of 24-hour sessions correlated for participating

stations

The distinction between these groups was made on
the assumption that results will be more meaningful forthe stations with more sessions. The Large N group account for 88 % of the station-days and is dominant indetermining the overall performance as shown in Table 1. The last two columns of the group analysis table indicate the number of stations that yield more than
90 % and less than 70 % of their data.

4 Historical performance
The 2018 performance is in line with historical data
yield (85 % – 88 %) as shown in Figure 3.

Table 1: Group analysis of data yield
Category
Number stations Station-days Average Median >92 % <70 %Big Large N (>40)
121064
86.9 % 91.6 %6
1Large N (≥17)
21
1283
86.1 % 84.6 %8
3
Small N (<17)
2917272.2 % 72.4 %7
12Full network
50
1455
84.9 % 79.4 % 1515

5 Data loss

The data losses were also analyzed by sub-systems foreach station but only network results are presented in
Figure 4. Computing data loss is not always straightforward. In some cases, down time is used to compute data
loss but for certain problems (warm receiver, pointing,RFI) the data loss is estimated from an approximate
equivalent number of recorded bits lost.
The antenna problems have been the major causeof data lost for almost 10 years. This is probably due toaging antennas. The miscellaneous category includes
problems that do not fit the other categories. These aremainly problems beyond the control of the station andis dominated by bad weather and scheduling conflicts.
The receiver data losses were due to three stations thatobserved with warm receivers for a total of 67 stationsdays.
Stations can receive their own results by contacting the authors.

2018 IVS Network Performance

6 RFIThis category includes all losses directly attributable
to interference. RFI is mainly evaluated from dropped
channels at correlation but there are some difficulties indistinguishing BBC and RFI problems. Some stations
were contacted to confirm RFI presence at site. RFI due
to commercial systems continues to be an importantfactor of data loss, mostly in S band. Table 2 provides
a short list of dropped channels at the most affected
stations in 2018.
Table 2: Most affected stations by RFI in 2018
Station
Data loss Most affected channels (frequencies in MHz)
Sejong18.0 % SR4U (2295 MHz), SR5U (2345 MHz), SR6U (2365 MHz)Kunming
13.9 % SR5U (2345 MHz), SR6U (2365 MHz), SR1U (2225 MHz)
Zelenchukskaya 13.0 % SR2U (2245 MHz), SR3U(2265 MHz), SR4U(2295 MHz)
Koganei1112.5 % No fringes in some sessions due to weak S band signal
affected by RFI
Yebes 40 m
8.7 % SR2U (2245 MHz), SR4U (2295 MHz)
Medicina
6.0 % SR6U (2365 MHz)
Hobart26
5.1 % SR5U (2272 MHz) SR6U (2288MHz) –AOV sessions
SR5U (2281 MHz) SR6U (2297 MHz) –CRDS sessions
SR5U (2345 MHz) SR6U (2365 MHz) –CRF, RD sessions
Matera
4.1 % SR6U (2365 MHz)
Wark12m
3.8 % SR5U (2345 MHz), SR6U (2365 MHz) –Intermittent
Fortaleza
3.1 % SR4U (2295 MHz) –Mostly in September-December

Channels: SR1U = band|polarization|BBC#|sideband

7 Summary
Estimating station data losses could be subjective andsome times approximative but is a useful tool for evaluating the health of the IVS network over the years. A
station yielding over 80 % of data is considered very
good and the statistics of the Large N group are showing that stations have been doing pretty well in 2018.

179

CONT17 From a VieVS Perspective
J. Böhm, M. Schartner

Abstract CONT17 is a special VLBI campaignof the International VLBI Service for Geodesy andAstrometry in November and December 2017 withthree independent networks. Two legacy networks with
14 stations each are observing at S- and X-band for
15 days, while a network with six stations is observing
in the new VGOS broadband mode. We investigate the
CONT17 schedules with the new scheduling software
VieSched++ to provide feedback on the legacy and
VGOS schedules. Finally, we generate a schedule formixed-mode observations which could be observedwith the CONT17 stations.

Fig. 1: CONT17 legacy network A (mostly VLBA) in red andnetwork B in blue. The figure is taken from https://ivscc.gsfc.
nasa.gov/program/cont17/ .

Keywords Scheduling · VGOS · Mixed-mode

1 Introduction
Two legacy networks observed at S/X band from 28
November until 12 December 2017 and one VGOS network did broadband observing over five days from 4 to
8 December 2017. The plan for the CONT17 campaign
was to acquire state-of-the-art VLBI data to demonstrate the highest accuracy of which the legacy S/X
VLBI system is capable, to investigate possible network
biases, and to demonstrate some of the VGOS capabilities limited by the size and geometry of the available
VGOS network and observation period.
Johannes Böhm · Matthias Schartner
Technische Universität Wien, Department of Geodesy andGeoinformation, Gußhausstraße 27–29, AT-1040 Vienna, Austria(Correspondence: johannes.boehm@geo.tuwien.ac.at)

Fig. 2: VGOS station network during CONT17. ONSA13NE has

been verifying the VGOS chain at the time of CONT17 and is
not used here. The figure is taken from https://ivscc.gsfc.nasa.
gov/program/cont17/ .

The legacy A network with 14 stations (mostly
VLBA, correlated in Socorro) observed at a data rateof 256 Mbit/s and the legacy B network, also with
14 stations (correlated in Bonn), used a data rate of
512 Mbit/s (see Fig. 1). On the other hand, the VGOS
network with six stations (see Fig. 2) observed at
8 Gbit/s and the baseband data were correlated at MIT
Haystack Observatory.
180

Scheduling CONT17 sessions

In this report, we focus on the schedules of the
CONT17 sessions which have been generated withsked (Gipson, 2010). Here, we use VieSched++(Schartner and Böhm, 2019) to check whether there
are improvements possible with those geodetic schedules. To assess both types of schedules, the simulation
tool of the Vienna VLBI and Satellite Software(VieVS) (Pany et al., 2011; Böhm et al., 2018) has
been applied with a refractive index structure constantof 1.8 · 10−7 m−1/3 and a constant scale height of 2 km
for all stations (Nilsson et al., 2007), a clock variation
corresponding to an Allan Standard Deviation of
10−14 at 50 minutes (Herring et al., 1990), and a white
noise per baseline observation of 30 picoseconds. The
Monte-Carlo simulation is always based on 500 runs.

2 Schedules for the legacy B network
The multi-scheduling mode of VieSched++ is used
to generate more than 1000 schedules with different
weight factors, such as different weights for skycoverage or the number of observations, for the firstday of CONT17 and the legacy B network. Out of
those schedules, 150 have been further tested with
Monte-Carlo simulations as described in Section 1.
Finally, we focus here on two schedules, namely v483
based on the same list of 100 sources as used by sked
and v036 using an extended list of 300 good sources.
Table 1 summarizes the number of observations andscans for the schedules.

181

Fig. 3: Simulated repeatabilities in microarcseconds for the

Earth orientation parameters for the schedules listed in Table 2.
The black bars correspond to the actually observed schedules, thered and blue bars to the schedules generated with VieSched++
with the same and the extended source lists, respectively.

ties, the improvement for the new schedules is not significant (not shown here).

3 Schedules for the VGOS network

work. The first line corresponds to the actually observed schedule, the other two lines correspond to variants generated with
VieSched++ with different source lists.
# obs# scans
C1701
13499
1499
v483
14921
1278
v036
15094
1478

We also scheduled one day of the VGOS network withthe following stations participating as core stations:
GGAO12M, WESTFORD, KOKEE12M, RAEGYEB.
Other stations (ISHIOKA, ONSA13NE, ONSA13SW,WETTZ13S) were added in tag-along mode as wasdone for the actual schedule with sked. In accordancewith the observed schedules, we used fixed values of
30 seconds for the scan times and the same down-timesof the antennas. However, for the VGOS schedules
generated with sked, a minimum slew time of 30 seconds was obviously set, too. While we understand theminimum scan lengths due to unknown fluxes at all frequencies, we do not follow the 30 seconds minimum
slew times because the purpose is not clear and there isno possibility to apply that constraint in VieSched++.

Figure 3 depicts the repeatabilities of Earth orientation parameters as derived with Monte-Carlo simulations. In general, there is an improvement with theschedules generated with VieSched++, which is evenmore pronounced when using an extended source list
for scheduling. In terms of station position repeatabili-

Finally, two schedules are presented here: v066
with the same source list as used by sked, and v058
with an extended list of good sources (more than
250 mJy). The increase in number of observations andscans with about 60 % is substantial. This effect ismainly due to the minimum slew times applied withsked but other differences like the varied applicationof sub-netting plays an important role, too. Monte-

Table 1: Characteristics of the schedules for the legacy B net-

182

Böhm et al.

Table 2: Characteristics of the schedules for the VGOS network.

The first line corresponds to the actually observed schedule withminimum slew times of 30 seconds, the other two lines correspond to variants with different source lists and without minimum slew times.
# obs# scans
17DEC03VS
12985
1180
v066
21041
1948
v058
21061
1985

Carlo simulations have not been carried out for theseschedules.

4 Schedules for mixed-mode
observations
We also generate schedules for mixed-mode observations for CONT17 as they could have been observed.
In the following, we assume that the legacy A network
is observing with data rates of 128 Mbit/s at X- andS-band and that the legacy B network is observing at
192 Mbit/s and 320 Mbit/s, respectively. Furthermore,
we assume that the channels observed by the legacy B
network comprise all channels observed by the legacy
A network. Finally, we assume that the VGOS network
is observing with a data rate of 2048 Mbit/s at S- andX-band, again including all channels observed by bothlegacy networks (cf. Fig. 3). Here, all integration times
have been calculated based on the channels, and no
special factor has been applied when observing withlegacy S/X stations (circular polarized receivers) and
VGOS stations (linear polarized) together.
Figure 4 depicts how many scans were observedwith how many stations. It is evident that there is ahigh number of scans with many stations participating,i.e., the networks are very well connected. The schedule presented here includes 2016 scans and 126592 observations at an average idle time of 2.4 %.
Table 3: Number of baselines possible with a mixed-mode sce-nario.
band
S
S
S
X
X
X

data rate
128 Mbit/s
192 Mbit/s
2048 Mbit/s
128 Mbit/s
320 Mbit/s
2048 Mbit/s# baselines
399
203
28
399
203
28

baselines
A-A, A-B, A-V
B-B, B-V
V-V
A-A, A-B, A-V
B-B, B-V
V-V

Fig. 4: Number of scans versus number of stations participatingin the scans. For example, there are 638 scans with three stations
and 64 scans with 30 stations.

5 Conclusions and outlook
We used the scheduling software VieSched++ (Schartner and Böhm, 2019) to assess the schedules generated with sked for CONT17. We could confirm that theschedules for the legacy networks are well optimized
and only smaller improvements are possible with VieSched++.
The situation is different for the VGOS schedules,
which could be greatly improved. It is not clear why
the VGOS schedules do have constraints of minimum
30 seconds for scan and slew times. In particular, theslewing time can be well derived from the antenna
specifications. Also a more sophisticated use of subnetting could improve the performance of the schedules.
It was also possible to generate a schedule in amixed-mode scenario, which connects all networks,
legacy and VGOS, in one schedule. This approach
might be a useful scenario for a CONT2020 campaign.
Acknowledgements The authors would like to acknowledge
the Austrian Science Fund (FWF) for supporting this workwithin project P31625.

Scheduling CONT17 sessions

ReferencesBöhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry. PASP,
130, 044503, doi:10.1088/1538-3873/aaa22b
Gipson J (2010) An Introduction to Sked. In: D. Behrend,
K. D. Baver (eds.): IVS 2010 General Meeting Proceedings,
NASA/CP-2010-215864, 77–84
Herring T, Davis J, Shapiro I (1990) Geodesy by radio interferometry: The application of Kalman Filtering to the analysis
of very long baseline interferometry data. J Geophys Res,95, 12561–12581, doi:10.1029/JB095iB08p12561

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Nilsson T, Haas R, Elgered G (2007) Simulations of atmospheric path delays using turbulence models. Proc. 18th
EVGA Working Meeting, 175–180
Nothnagel A, Artz T, Behrend D, et al. (2017) International
VLBI Service for Geodesy and Astrometry. J Geod, 91,
711–721, doi:10.1007/s00190-016-0950-5
Pany A, Böhm J, MacMillan D, et al. (2011) Monte Carlo simulations of the impact of troposphere, clock and measurement
errors on the repeatability of VLBI positions. J Geod, 85,
39–50, doi:10.1007/s00190-010-0415-1
Schartner M, Böhm J (2019) VieSched++: A New VLBI
Scheduling Software for Geodesy and Astrometry. PASP,
131, 084501, doi:10.1088/1538-3873/ab1820

The IERS Rapid Service / Prediction Centre UT1−UTC
Combined Solution: Present and Future Contributions
M. Davis, M.S. Carter, C. Dieck, N. Stamatakos

Abstract The IERS Rapid Service / Prediction
Centre (RS/PC) is responsible for producing a daily
combined-solution for Earth Orientation Parameters(EOP), including UT1−UTC. The daily RS/PC EOP
solution is designed to produce the most accurate,
precise, and robust EOP solution for a given day
using the most up-to-date observations and models
available. A high-quality 0-day UT1−UTC solution
requires low-latency observations that can consistently
produce accurate and precise UT1−UTC values.
However, the IVS Intensives and UTGPS data series
are the only two low-latency UT1 or UT1-like data
sources, respectively, used in the RS/PC combined
solution. Due to the importance of low-latency datain our Daily UT1−UTC Combination, we are investigating additional low-latency VLBI baselines thatcan robustly contribute to the UT1−UTC solution
in circumstances where the standard IVS antennas
become unavailable. To that end, we are in the processof characterizing a potential backup Intensive series
using the VLBA Mauna Kea antenna together with the
20-meter Wettzell and new Wettzell North 13-meter
antennas. If the characterization is successful, this will
provide additional alternative baselines for operationaluse in the future, should they be necessary.

Keywords UT1−UTC · Combined-solution · Intensives · UTGPS

1 Introduction
The IERS Rapid Service / Prediction Centre (RS/PC)
has been charged by the International Earth Rotation
and Reference Systems Service (IERS) with producing a high-quality, daily Earth Orientation Parameters (EOP) solution available to the public (IERS Central Bureau, 2017). The RS/PC produces a daily andweekly EOP solution for Polar Motion x and y (PMx, PM-y), UT1−UTC, Length of Day (LOD), and Celestial Pole Offsets (dψ, d and dX, dY) (Table 1). Finals.daily is generated and verified 365 days a year by
17:30 UTC using the most recent EOP measurements

Table 1: IERS Rapid Service / Prediction Centre EOP Combina-

tion Products and Distribution Frequency
Product

Distribution
Frequency· 7 Combination days
· 1 year of Predictions∗

Bulletin A(ser7.dat)
finals.all†finals2000A.all††finals.data†

Maria Davis · Merri Sue Carter · Nick Stamatakos
U.S. Naval Observatory, IERS Rapid Service / Prediction Centre,
3450 Massachusetts Ave NW, Washington, D.C., 20392 U.S.A.
Christopher Dieck
U.S. Naval Observatory, USNO VLBI Analysis Center, 3450
Massachusetts Ave NW, Washington, D.C., 20392 U.S.A.
(Correspondence: maria.a.davis33.civ@mail.mil)· Begins in 1973
weekly(Thursdays by
19:00 UTC)

finals2000A.data††
finals.daily†

Description· EOPs re-calculated
1 year in past
· Begins in 1992
· EOPs re-calculated
1 year in past

Daily

finals2000A.daily†† @ 17:30 UTC· 90 Combination days
· 90 Prediction days

† Celestial Pole Offsets calculated in dψ, d†† Celestial Pole Offsets calculated in dX, dY* Excluding dX, dY and dψ, d

184

IERS RS/PC UT1−UTC Combined Solution

185!"#$%&%'()*+,- %(!.,-/!"#&()!.,-/

0$(%(01

Fig. 1: Residuals of each Contributor after systematic corrections have been applied w.r.t. the Daily RS/PC UT1−UTC combinedsolution (finals.daily). Analysis files from each Contributor are filtered to only include expected (or standard) baselines. The combined 0-day solution (indicated by the vertical dotted line) could be negatively impacted if the low-latency Intensives are not available
and the solution is thus primarily dependent on the (currently) noisy UTGPS series. Table 2 provides a description of shorthand usedin this figure.

and models from RS/PC Contributors. EOP solutions,whose accuracy are not verified prior to release, arealso generated daily at 03:10, 09:10, and 21:10 UTC.
While much of the discussion in this paper will also
apply to the UT1−UTC values in our weekly products(Table 1), our focus will be on the unique requirements
related to generating a quality daily UT1−UTC. The
RS/PC produces and disseminates a number of otherproducts that will not be discussed here; however, they
can be found at https://maia.usno.navy.mil/ser7.
Each data series with a UT1−UTC value provided
to the RS/PC by a Contributor has been assigned aweight indicating the influence the data series will
have in the combined-solution, and systematic corrections to correct for any offsets from the reference
series. The EOP contributions are combined using
a weighted smoothing cubic spline (McCarthy andLuzum, 1991) to generate the daily combined-solution.
Figure 1 shows an example of the residuals of each
UT1−UTC Contributor with respect to (w.r.t.) the
daily combined-solution (finals.daily); the verticaldotted line indicates the 0-day solution’s epoch.
The 0-day solution is considered to be the EOP
combined-solution at the midnight epoch of the day
the Combination is generated. Figure 1 also lists thebaselines or series used from each IVS Analysis Center(Contributor) to generate the daily combined-solution.
The RS/PC filters VLBI analysis files provided byAnalysis Centers of the International VLBI Service
for Geodesy and Astrometry (IVS) by baseline (for*.eopi files) or series (for *.eoxy files) and applies asingle systematic correction to each Contributor prior
to generating the Combination. Alternate baselines
may be integrated into the combined-solution if thebaseline has been characterized, and sufficient notice
has been provided by the IVS Coordinating Center.

2 Generating a combined solution for
UT1−UTC
Generating a consistent, high-quality daily UT1−UTC
solution is non-trivial due to the challenge of obtain-

186

Davis et al.

ing robust, low-latency contributions. Low-latency
Contributors currently used by the RS/PC for the
UT1−UTC combination are 1) the 12 UTC Ultra-rapid
UTGPS series (UTGPS − a UT1-like value) generated
by U.S. Naval Observatory (USNO) GPS Analysis
Division, 2) the International GNSS Service (IGS)
Ultra-rapid integrated LOD values, 3) combined
Atmospheric Angular Momentum (AAM) predictions
from the National Centers for Environmental Prediction (NCEP) and Navy Global Environmental Model(NAVGEM), and 4) the IVS VLBI INT1, INT2, and
INT3 (Table 2) Intensives analyzed by Goddard Space
Flight Center (GSFC), the Geospatial Information
Authority of Japan (GSI), and the USNO. A timeline
sketch in Figure 2 shows the regularly available lowlatency Contributors utilized in the daily UT1−UTC
solution. We will define low-latency contributions here
to be processed and available observations or models
that have a midpoint epoch within 24 hours of the
Daily Combination, which begins at 17:00 UTC.
While the IGS Ultra-rapids, UTGPS, and AAM
contributions are available daily, there are data delays and gaps in scheduled IVS Intensives due to station maintenance, local station national holidays, severe weather, or unforeseen station or internet outages.
Hence, IVS Intensives cannot be included in the Combination when these events occur, leaving the remaining low-latency Contributors to determine the 0-day

Table 2: A brief description of shorthand used to describe VLBI

observations by session-type (e.g., R1 or INT3) or baseline (e.g.,
KkWz) as they are used in this paper. (INT = Intensive; BL =Baseline)
Baseline or
Session
Kk
Wz
Wn
Is
Mk
Ny
KkWz
IsWz
MkWz
MkWn
R1
R4
INT1
INT2
INT3

Description· 20 m Kōke‘e Park Radio Telescope· 20 m Wettzell Radio Telescope· 13 m Wettzell North Radio Telescope· 13 m Ishioka Radio Telescope· 25 m VLBA Mauna Kea Radio Telescope· 20 m Ny-Ålesund Radio Telescope· Kōke‘e–Wettzell BL INT· Ishioka–Wettzell BL INT· Mauna Kea–Wettzell BL INT· Mauna Kea–Wettzell North BL INT· Multi-BL session; begins Monday· Multi-BL session; begins Thursday· Single-BL session; Monday–Friday· Single-BL session; Saturday–Sunday· Single-BL session; Monday

Duration

1 hr
1 hr
1 hr
1 hr
24 hr
24 hr
1 hr
1 hr
1 hr

(KkWz)-1-daySolution

IVS INT1
Observation

00:00

19:00

(IsWz)
RS/PC Daily
0-day IVS INT2/3 Combination
Solution Observation Generated

00:00

UTGPS / IGS Ultra Rapid
Solution

08:00

12:00 17:00

UTC

AAM Predictions(7.5 days)

Fig. 2: Timeline of approximate midpoint epochs of UT1−UTC

low-latency Contributors w.r.t. the 0-day UT1−UTC solution andthe beginning of the Daily Combination. The RS/PC primarily
utilizes the KkWz baseline for the INT1 series, and the IsWz baseline for the INT2/INT3 series (Table 2). The RS/PC Daily Combination begins every day at 17:00 UTC and is nearly always
published by 17:30 UTC (Table 1). If the Intensive processing
is delayed or unavailable for a given day, UTGPS, IGS Ultrarapids, and AAM predictions determine the 0-day solution for
UT1−UTC.

UT1−UTC solution. While the techniques utilized bythese remaining Contributors are valuable in generating a high-quality 0-day solution, none of them are able
to directly measure UT1−UTC as VLBI Intensives do.
Therefore, any loss of IVS Intensives longer than 1−2intermittent days can have significant and long-term
impacts on the UT1−UTC time series, particularly if
the lost Intensives are not in proximity to an IVS 24hour R1 or R4 session, which would eventually compensate for the missing data (Stamatakos et al., 2015).
In 2018, new Intensives were available prior to the beginning of the Daily Combination at 17:00 UTC 69 %of the year.
The effect of losing low-latency Intensives in thedaily UT1−UTC combined-solution is observed in2015 when the Kōke‘e station (Kk) was unable totransmit their Intensives data electronically due to aninternet outage from June 2014−January 2016, andwas forced to mail their Intensives to the Washington
Correlator. While the reference series, finals.data(Table 1), appears to not be significantly impacted
by the increased Intensive latency w.r.t. the previous
recent years, the 0-day daily solution was substantiallyinfluenced (Stamatakos et al., 2014, 2015, 2016).
Increased noise in the UTGPS data series beginningmid-2015 (Davis and Stamatakos (2017)) also exacerbated the impact of the delayed INT1 Intensives.
As we previously discussed, and can be visualizedusing Figures 1 and 2, consistent delays of 2−3 days in
INT1 Intensives forces the 0-day UT1−UTC solution
to become dependent on UTGPS, integrated IGS
Ultra-rapid LOD, and AAM predictions. The mean

IERS RS/PC UT1−UTC Combined Solution

and standard deviation of the annual 0-day daily
UT1−UTC solution residuals w.r.t. the C04 each show
a 19 µs increase from 2013 (Stamatakos et al., 2014)
to 2015 (Stamatakos et al., 2016). This corresponds toa 950 % and 51 % increase in the mean and standard
deviation from 2013, respectively. However, the 2015
UT1−UTC 0-day solution would have likely beensignificantly less degraded if the UTGPS series had
been less noisy or the INT1 Intensives maintained
their expected latency of < 22 hours.

187
Current
INT
GSFC
24 hr

"##$%&'()*$+,*-)*))+.,&/+$0*1

INT1
INT2
INT3
R1
R4

sessiontypebaseline

SettingParameters:! Systematic
Corrections! Weighting

FutureFig. 3: Current and future flow of VLBI data in the RS/PC
combined-solution, using GSFC as an example. Future additions
are shown as shaded boxes. The RS/PC currently filters each data
file provided by the Analysis Centers for specific baselines orsession-types and then applies a single systematic correction andweight to the data series. In the future, we will be able to apply
weights and systematic corrections to specific sets of data identified by session-type or characterized baseline.

3 Creating a more robust UT1−UTC
solution
There are several improvements in development to increase the robustness and general health of the daily
UT1−UTC combined-solution. One modification thatcan be made to make the Combination more agile is toimplement a more granular application of weights andsystematic corrections (i.e., minor adjustments used toremove any residual corrections not accounted for at
the analysis level) to Contributor’s VLBI data sets.
Currently, our Daily Combination uses a whitelist filter
on a given analysis file so that only desired sessiontypes (e.g., R1) or baselines (e.g., KkWz) are includedin the Combination process. Then, a single weighting and set of systematic corrections are applied to
the whole series. E.g., A GSFC Intensive analysis fileis filtered to only include KkWz and IsWz (Table 2)baselines, and then a single weight and set of systematic corrections are applied to both baselines. Consequently, it is difficult to include non-standard baselines
or series in the RS/PC Combination as they first need
to be verified as having similar systematic corrections
to the standard baselines. However, if we apply systematic corrections and assign weights by session-type
and/or baseline, we will be able to more easily integrate new baselines into our Combination. The sketch
in Figure 3 demonstrates the RS/PC’s current and desired future method for utilizing multiple baselines andsession-types.
Developing consistent, reliable backup baselines
for the INT1 and INT2 Intensives that can be utilized
when the standard baselines are unable to observe will
also improve the robustness of the 0-day UT1−UTC
solution. Ishioka and Kōke‘e stations are currently able
to substitute for one another, while Ny-Ålesund or
Wettzell North stations can potentially substitute for

Wettzell. However, the RS/PC needs to work with the
IVS to determine “official” Intensive baseline backups,
characterize those baselines, and be prepared to implement them in our Daily Combination with little notice.

3.1 Integrating a new VLBI Intensive
baseline into the RS/PC
combination
Prior to any new series or baseline being used in the
RS/PC EOP Combination, we must “characterize” thesession-type or baseline to determine 1) its systematic
corrections w.r.t. the reference series and 2) if the newbaseline or session-type significantly varies from thestandard baseline or session-type already utilized fromthe given Analysis Center (e.g., does the KkWn baseline vary significantly from the KkWz or IsWz baseline in the GSFC analysis file?). However, the RS/PC
is currently developing software modifications, shownin Figure 3, to apply unique systematic corrections to agiven session-type or baseline, eliminating the requirement for (2) above. An ideal data sample to characterize an Intensive baseline would include 100−200 observations over a 1−2 year period. However, the RS/PC
only requires 60 observations over a minimum 4 month
period, as an ideal sample size is impractical in manycases.
The USNO, IVS, and National Radio Astronomy Observatory (NRAO) are working together tocharacterize MkWz and MkWn (Table 2) baselines.
These baselines are designed to quickly substitutefor a Kōke‘e or Ishioka station outage or schedulingconflict. We were particularly interested in utilizing
the VLBA Mauna Kea antenna due to its geographic

188

location and proximity to Kōke‘e station; Mauna
Kea is on the Eastern side of Hawai‘i at 4205 meters
above sea level, and has often been able to continue
observing when Kōke‘e has had to shut down due tosevere weather conditions. However, Mauna Kea’s
proximity to the Kilauea volcano has presented somechallenges, as the station has moved due to Kilauea’s
volcanic activity in mid-2018. Dieck et al. (2019)
discusses some of these challenges and describes
the design of the MkWz / MkWn characterization
sessions.

3.2 Improving UTGPS series
The UTGPS UT1-like data series (Kammeyer (2000))is an invaluable contribution to producing a robust andreliable 0-day solution. As discussed in Section 2, UTGPS is the primary series used to determine the 0-day
UT1−UTC value on days when a low-latency Intensive is unavailable. Data reliability is another advantage to using this data series, as there are only 2 daysin 2018 when a solution was not available prior to the
RS/PC Combination. UTGPS also generates 4 series
each day, corresponding to the IGS Ultra-rapid production schedule. While the RS/PC only currently utilizes
the 12 UTC UTGPS solution, we could potentially include the other three series calculated at the remaining
quarter-day epochs.
However, the 12 UTC UTGPS UT1-like series has
been very noisy since mid-2015, contributing to the decrease in the 0-day UT1−UTC solution quality (Davisand Stamatakos, 2017). The USNO GPS Analysis Division is currently investigating model-level modifications to improve the accuracy of the UTGPS data series, and the RS/PC is exploring revisions to the UTGPS pre-processing methodology used to account for
the inherent time-series drift. While updates to the
RS/PC preprocessing procedure may result in minor
series improvements, our initial investigations with the
GPS Analysis Division suggest that the UTGPS model
requires updating to improve its accuracy.

4 Concluding thoughts
IVS Intensives are incredibly important to the healthof the RS/PC UT1−UTC product. With improvements
to integrating individual baselines into the RS/PC’s

Davis et al.

Combination, and consistent and reliable low-latency
backup Intensive baselines cultivated by the IVS, the 0day UT1−UTC solution produced by the RS/PC should
continue to improve in accuracy and precision. Although currently noisy, UTGPS generally provides an
excellent low-latency check on the IVS Intensives andacts as a good backup when Intensives are unavailable.
As a final thought, the RS/PC would potentiallybe interested in a Southern Hemisphere Intensive observing simultaneously with the Northern Hemisphere
INT1 series. The Southern Hemisphere Intensive could
act as a corroboration and backup to the Northern
Hemisphere Intensives.
Acknowledgements The authors would like to acknowledge
the efforts of Nathan Shumate, Megan Johnson, Andrew Sargent,
Jeffrey Tracey, Sharyl Byram, and NVI Inc who directly and indirectly contributed to the work presented in this paper.

References
Davis M, Stamatakos N (2017 September 25–27) Improving the
IERS Rapid Service / Prediction Center UT1−UTC 0-Day
Solution. Paper presented at Journees 2017, des Systemes deReference et de la Rotation Terrestre: Furthering our knowledge of Earth Rotation, University of Alicante, Spain
Dieck C, Johnson M, Davis M, et al. (2019) Intensive sessions
with the Mauna Kea VLBA Station. In: R. Haas, S. GarciaEspada, J. A. López Fernández (eds.): Proc. 24th EVGA
Working Meeting, 152–156
International Earth Rotation and Reference Systems Service(IERS), Central Bureau Appendix 1: IERS Terms of Reference. In: W. R. Dick, D. Thaller (eds.): IERS Annual Report
2017, 177–183
Kammeyer P (2000) A UT1-Like Quantity from Analysis of
GPS Orbit Planes. Celest. Mech. Dyn. Astr., 77, 241−272
McCarthy D D, Luzum B J (1991) Combination of precise observations of the orientation of the Earth. Bulletin Gèodèsique65, 22−27 doi:https://doi.org/10.1007/BF00806339
Stamatakos N, Carter M S, Shumate N (2014) Rapid Service/Prediction Centre. In: W. R. Dick, D. Thaller (eds.)
IERS Annual Report 2013, 65−82
Stamatakos N, Davis M, Shumate N, et al. (2015) Rapid Service/Prediction Centre. In: W. R. Dick, D. Thaller (eds.):
IERS Annual Report 2014, 70−72
Stamatakos N, Davis M, Shumate N, et al. (2016) Rapid Service/Prediction Centre. In: W. R. Dick, D. Thaller (eds.):
IERS Annual Report 2015, 79−81

Analysis of Intensive Sessions at BKG
A. Girdiuk, D. Thaller, D. Ullrich, G. Engelhardt, R. Wojdziak, C. Plötz

Abstract Currently hourly intensive sessions monitor Earth Rotation variations every day almost without breaks. Regular intensive sessions INT1, INT2 andINT3 collect data on various networks at different daysof the week. The goal of the analysis of these intensive
sessions is to monitor ongoing changes in dUT1. The
Analysis Centers are obligated to provide estimates ofdUT1 with very low latency which implies the productrelease on the same or next working day. These dUT1
variations are obtained by solving each intensive independently. Here we examine all intensive sessions andthe corresponding parameterization.

Keywords Intensive sessions · Parametrization · dUT1

1 Introduction
The main purpose of intensive session analysis is toprovide information on rapid changes in Earth Rotation. These special VLBI experiments are regular observations of about one hour duration. Recently, longer
sessions INT1* (Dieck et al., 2019) started to observe
over 1.5 h till 2 h. The first intensive experiments havebeen commenced in 1999. The session duration, network and final results were investigated on their basis,so that in 2002 the first regular intensives, now known
as INT1, have been started. Intensives INT1 are run on
Anastasiia Girdiuk · Daniela Thaller · Dieter Ullrich · Gerald Engelhardt · Reiner Wojdziak · Christian Plötz
Federal Agency for Cartography and Geodesy (BKG), RichardStrauss-Allee 11, DE-60598 Frankfurt am Main, Germany(Correspondence: Anastasiia.Girdiuk@bkg.bund.de)

weekdays at 18:30 UT. Shortly after the INT1 started
the weekend gap was filled with intensives INT2. Theirobservations begin at 7:30 UT and are of the same onehour duration. The majority of these intensives employs 2 stations only. A small amount of INT1 experiments is observed in a 3-station network, mainly
for test purposes only. In almost all intensives the core
VLBI station at Wettzell participates and the second
station is varied. The antenna in Wettzell is chosen because of the high stability governed by clock reliability, technical antenna specifications and high quality
continuous maintenance. The first intensives were observed with NRAO20 or Kokee as the second station,
and a few of them with Tsukub32. On the basis of theseexperiments only 1 baseline Wettzell – Kokee was selected for intensives INT1. Over the whole time spansome other stations, Svetloe, Nyales20, Tsukub32 andWettz13N, participated for a short time in INT1 during the maintenance periods of the main stations. The
other intensives, INT2, were observed mostly on thebaseline Wettzell – Tsukub32 in the beginning. Later,
Wettzell and Ishioka participated in INT2 observations
more frequently, so that Ishioka replaced Tsukub32.
Occasionally Kokee takes part in these experiments aswell. To improve the accuracy of dUT1 estimates amodification of intensives is required. The idea is to
get more observations and a better network geometry.
The majority of these INT3 sessions are observed ina 3-station network including Wettzell, Tsukub32 andNyales20. The most recent experiments gather observations in more than 4-station networks, with Ishioka,
Wettz13N and Svetloe. These efforts allow to achieve
an unprecedented amount of observations (about 150
per session), compared to earlier intensives. However,most of the INT3 experiments collect about 70–80 observations.

189

190

Here, we investigate the characteristics of the intensives session, such as number of observations, participating antennas and observed sources. Besides this, theterrestrial and celestial reference frames are reviewed
for the parametrization of intensive sessions.

2 Intensives time series
The BKG Analysis Center assembles time series of allintensives starting with the first experiments in 1999
(Table 1). Among all observed and correlated experiments this time series includes only intensives analyzed at BKG Analysis Center. All experiments are analyzed with the same approach in a uniform way. Thus,
only a few unresolved sessions are excluded due to asmaller number of observations than unknowns. Also,
because the routine analysis cannot incorporate INT3
sessions that are only provided in vgosDb format, 30of these experiments are missing since 2018, and in
total 470 intensives INT3 are analyzed. Besides this,the most recent INT* experiments are processed andincluded in the current BKG time series as a part ofintensives INT1.
Based on the analysis of the intensives time series,
the distributions of observations (time delays), sources,
and stations per session are illustrated (Fig. 1). Relative numbers in percentage are expressed as parts ofall sessions. In most of intensives INT1 the number ofobservations is about 18 delays per session obtainedin 32 % of all intensive sessions. A large number ofabout 32 delays per session are collected in experiments INT2 which represent only 7 % of the complete data set. Even more observations per session, 70–
80, are collected in experiments INT3 which represent
only 2 % of all intensives.
This distribution indicates that a larger number ofsources per session observed in INT2 may induce theincrease in the number of time delays per session. A
larger number of sources can be observed using a betterscheduling algorithm, or faster antennas, or also moreantennas. The number of sources observed in INT3 increased w.r.t. INT1 twice, and w.r.t. INT2 by 50 %.
At the same time, observations in 3-station networks
reveal approximately the same amount of 4 % of theINT1 and INT3 sessions. Intensives INT3 collect the
majority of observations with 3 stations, while only 4

Girdiuk et al.
Table 1: Intensive sessions. Data amount includes all experi-ments at BKG Analysis Center until February 2019.
Mon Tue Wed Thu Fri Sat Sun Amount ofexperiments
INT3
470
INT1*
INT1* INT1*
10
INT1 INT1 INT1 INT1 INT1
3760
INT2 INT2 1490
intensives before 2002
700
* new INT1 sessions.

and 5 station networks allow to obtain 70 and more observations.
Fig. 2 shows regular station attendance in each intensive experiment. Wettzell takes part in almost all experiments as expected. The second antenna in the firstintensives is NRAO20 in more than half of cases andKokee in the rest of them. Their successor INT1 shows
an overwhelming majority of sessions on the Wettzell– Kokee baseline. Nyales20, Svetloe and Tsukub32 areused as 3rd station in 10 % of the INT1. INT2 was designed to employ a different network with the same
core station at Wettzell. Tsukub32 is included mostly
as the second station (75 %). Kokee and Ishioka participated in INT2 in approximately equal parts (10 %). It
is seen that INT3 combines stations observed in INT1
and INT2. The core of the network is represented already by 3 stations: Wettzell, Nyales20 and Tsukub32,
where Wettzell participates in most of experiments aswell. Moreover, the new small 13 m antenna at Wettzell
also successfully participates in 7 % of sessions INT3
together with the main dish and alone.

3 Parametrization
The parametrization applied in the routine analysis isdefined by the currently valid set labeled as bkgint14(Nothnagel, 2008). This set of parameters is utilized
by the BKG Analysis Center to provide corresponding products for the IVS. A priori models are appliedin agreement with the IERS Conventions (Petit andLuzum, 2010), with VTRF2008a (Böckmann et al.,2010) for station positions and velocities and ICRF2(Fey et al., 2015) for source positions (Table 2). Since
intensives have to be processed as soon as the correlation data is released the usage of predicted Earth
Orientation Parameters (EOP) time series is requiredAnalysis of Intensive Sessions at BKG

191

Fig. 1: Distribution of observations, sources and stations per session relatively to the number of all sessions in dependence on theintensives: first intensives INTs, INT1, INT2 and INT3.

as specified by Bulletin A (Dick and Thaller, 2017).
This time series known as usno finals.erp is adopted inthis analysis as provided by the Goddard Space Flight
Center (GSFC) group. The real meteorological data (ifavailable) or the Vienna mapping functions (VMF1,
Böhm et al., 2006) are applied for troposphere correction modelling in form of TRP files from GSFC (Thorandt et al., 2017).
Models employed in the current parametrization
demand an update, in particular, alternatives for TRF
and CRF are discussed here. The set of estimatedparameters in the routine analysis includes clock
polynomials up to 2nd degree, estimated per station

Fig. 2: Distribution of station attendance within intensive type.

Table 2: Parametrization of Intensive Sessions.

Parameter
Status A priori corrections
Earth orientation dUT1 Yes GSFC time series
Station clocks
Yes NoBaseline clocks
No
No
Zenith troposphere
Yes VMF1
Troposphere gradient No
VMF1
Terrestrial frameNo
VTRF2008a
Celestial frame
No
ICRF2

except the clock reference station. In almost all cases
we prefer to select Wettzell as the reference station.
Additionally, one offset is estimated for atmosphericparameters and one for dUT1. This parametrization

192

gives feasible variations of the dUT1 estimates
and their corresponding formal errors (Fig. 4). The
majority of the dUT1 estimates are obtained within±100 µas limit (Fig. 5, left). The formal errors are
smaller for INT2 and even smaller for INT3. The
numerous discrepancies of dUT1 estimates stemfrom the lack of reliable station positions. A priori
corrections to the station positions as provided by
VTRF2018 (Bachmann et al., 2016) and ITRF2014(Altamini et al., 2016) are considered to influence
the dUT1 estimates. The results are shown in Fig. 5
using the same time series of dUT1 estimates where
the applied station positions are varied only in theparameter set. The dUT1 estimates are highlighted
w.r.t. the station participated in the session. The current
time series (Fig. 5, left) suffers from the lack of 24
hour experiments where Ishioka participates, because
the applied internal method at BKG produces realtime coordinates for Ishioka and Tsukub32 (Engelhardt et al., 2016) on the basis of the most recent 24hour experiments. VTRF2018 reduces considerably
dUT1 estimates as expected since it is the VLBI
intra-technique combined TRF. ITRF2014 based on
the other geodetic techniques besides VLBI reports
additional numerous discrepancies for Wettzell. Lastly,
an impact of source positions is calculated based on
the newly released ICRF3 (Charlot et al., 2018). dUT1
estimates obtained in intensives with Ishioka andTsukube32 are not plotted on Fig. 3. The resulting
respective differences are assumed to be negligible
because of their large formal errors.

4 Conclusions and outlook
At this moment the time series of intensives reportedby the BKG Analysis Center includes a decent set ofobservations notwithstanding a growing lack of sessions that are provided in vgosDb format only. The
overview of intensive sessions INT1, INT2 and INT3
indicates the observation number growth, especially on
4 and more antenna networks. The dUT1 formal errors
in larger networks show a smaller variations which require a more detailed investigation of the network configuration and scheduling.
The parametrization of the intensive sessions was
examined with focus a on terrestrial and celestialreference frames. The VTRF2018 demonstrates better

Girdiuk et al.

Fig. 3: Differences in dUT1 estimates. The estimates calculatedusing ICRF2 subtracted from estimates based on ICRF3. A priori
ICRF is the only distinction in applied parametrization.

reduction, except special cases for Tsukuba coordinates which are best treated in a specially designed
internal adjustment at BKG. Thus, for the time being
VTRF2018 can be used as an intermediate solution to
replace VTRF2008a while a better approach will be
developed. The ICRF3 parametrization test illustrates
no significant variations in terms of dUT1 differences(Fig. 3).

References
Altamini Z, Rebischung P, Métivier L, et al. (2016) ITRF2014: A
new release of the International Terrestrial Reference Framemodeling nonlinear station motions. J Geophys Res: Solid
Earth, 121, 6109–6131, doi:10.1002/2016JB013098
Bachmann S, Thaller D, Roggenbuck O, et al.
(2016)IVS contribution to ITRF2014.
Current
intra-technique
combinationisavailable:
https://ccivs.bkg.bund.de/index.php?uri=quarterly/vtrf
J Geod, 90(7):631–654, doi:10.1007/s00190-016-0899-4
Böckmann S, Artz T, Nothnagel A (2010) VLBI terrestrial reference frame contributions to ITRF2008. J Geod, 84, 3, 201–
219, doi:10.1007/s00190-009-0357-7
Böhm J, Werl B, Schuh H (2006)
Troposphere mapping functions for GPS and VLBI from ECMWF operational analysis data. J Geophys Res, 111, B02406,
doi:10.1029/2005JB003629

Analysis of Intensive Sessions at BKG

193

Fig. 4: Variations of dUT1 estimates on the left side and their formal errors on the right side.

Fig. 5: Variations of dUT1 estimates: VTRF2008a, VTRF2018 and ITRF2014 (left to right).

Charlot et al. (2018) ICRF3 Documentation. in preparation for
Astron. Astrophys, http://hpiers.obspm.fr/icrs-pc/newwww/
icrf/index.php
Dick W, Thaller D (eds.) (2017) IERS Annual Report 2017.
International Earth Rotation and Reference Systems Service,
Central Bureau. Frankfurt am Main: Verlag des Bundesamtsfür Kartographie und Geodäsie
Dieck C, Davis M, Johnson M, et al. (2019) Intensive sessions
with the Mauna Kea VLBA Station. In: R. Haas, S. GarciaEspada, J. A. López Fernández (eds.): EVGA Proc. 24th
EVGA Working Meeting, 152–156
Engelhardt G, Thorandt V, Ullrich D (2016) Refinement of
the rapid UT1 estimation derived from Tsukuba VLBI measurements after the 2011 earthquake. In: D. Behrend,
K. D. Baver, K. Armstrong (eds.): IVS 2016 General Meet-ing Proceedings, NASA/CP-2016-219016, 225–228
Fey A, Gordon D, Jacobs C, et al. (2015) The Second Realizationof the International Celestial Reference Frame by Very Long
Baseline Interferometry. AJ, 150, 58, doi:10.1088/00046256/150/2/58
Nothnagel A (2008) Short Note: Conventions on thermal expansion modelling of radio telescopes for geodetic and astrometric VLBI. J Geod, doi:10.1007/s00190-008-0284-z
Petit G, Luzum B (eds.) (2010) IERS Conventions (2010). IERS
Technical Note, 36, Frankfurt am Main: Verlag des Bundesamts für Kartographie und Geodäsie.
Thorandt V, Engelhardt G, Ullrich D, et al. (2017) BKG/IGGBVLBI Analysis Center. In: K. D. Baver, D. Behrend,
K. L. Armstrong (eds.): IVS 2015+2016 Biennial Report,
NASA/TP-2017-219021

Scheduling of Twin Telescopes and the Impact on
Troposphere and UT1 Estimation
A. Corbin, R.Haas

Abstract Recently, several VGOS twin telescopes in
Europe were completed. We examine the use of VGOS
twin telescopes by a new scheduling approach. This approach is based on integer linear programming and creates uniform distributed observations over time. Several VLBI intensive sessions are rescheduled involving
the VGOS twin telescopes and the impact on the troposphere and UT1 estimation is investigated.

Kokee
IshiokaNy Ålesund

Keywords VLBI Intensive Sessions · VGOS Twin
Telescopes · Scheduling · Simulation · AtmosphericTurbulence · Global Optimization

OnsalaWettzellFig. 1: Map of the northern hemisphere showing the position

1 Introduction
VLBI intensive (INT) sessions (Schnell, 2006) are one
hourly sessions that are used to provide information
about the solar time UT1 on a regular basis and withlow latency. From Monday to Friday the INT1 baseline from Wettzell to Kokee is observed and on theweekend the INT2 baseline from Wettzell to Ishioka.
These baselines have large east-west components ensuring a high sensitivity to the solar time UT1. See
Fig. 1 for the location of the telescopes. Currently, thelegacy S/X setup is used for all INT sessions, howArmin Corbin1 · Rüdiger Haas
Chalmers University of Technology, Department of Space, Earthand Environment, Onsala Space Observatory, SE-439 92 Onsala,Sweden(1) now at: Universität Bonn, Institut für Geodäsie undGeoinformation, Nußallee 17, DE-53115 Bonn, Germany(Correspondence: corbin@geod.uni-bonn.de)of all observatories with VGOS twin telescopes (triangles) andobservatories with one only VGOS telescope used for the INT1
and INT2 sessions (circles).

ever, at each of the stations involved in the INT1 and
INT2 sessions a modern VGOS-compatible telescopeis available. Thus, it is possible to observe broadband
INT sessions. Moreover, there are VGOS twin telescopes at Wettzell enabling simultaneous observationof the INT1 and INT2 baselines. In total there are three
twin telescopes on the globe, which are all located inEurope (Fig 1). Involving both the VGOS twin telescopes at Wettzell and Onsala, as well as the VGOS
telescopes at Kokee and Ishioka, four baselines withlarge east-west component can be observed simultaneously.
We created new schedules for 187 INT sessions of
the year 2018. For each of these sessions three different
schedules were created. One without twin telescopes,
one with the twin telescopes in Wettzell and another194

Scheduling of Twin Telescopes

one with the twin telescopes in Wettzell and Onsala.
We used a new scheduling approach capable of finding
the schedule with the best sky coverage score (Sec. 2).
In the next step, the observations of each schedule were
simulated (Sec. 3). The simulator ensures that the atmosphere and the clocks for each session are independent of the schedule. Finally, the simulated observations were adjusted and the estimated parameters werecompared (Sec. 3). All computations were done with
the VLBI analysis toolbox ivg::Ascot (Halsig et al.,2017).

2 Scheduling
For each investigated INT session three different
schedules were created. The main difference between
them is the number of involved twin telescope stations.
Thus, we call the scenarios ZT (zero twin), OT (onetwin), and TT (two twins).
In the ZT scenario the same observatories as in theoriginal INT schedules are used, but with the VGOS
instead of the S/X legacy telescopes.
In the OT scenario the INT1 and INT2 baseline areobserved simultaneously with the VGOS telescopes in
Kokee and Ishoika and the VGOS twin telescopes in
Wettzell.
Finally, in the TT scenario the VGOS twin telescopes in Wettzell and Onsala as well as the VGOS
telescopes in Ishioka and Kokee are used. In this scenario four baselines with large east-west component
are observed simultaneously. To improve the sky coverage we also observe the short baselines between thetwin telescopes in Onsala and Wettzell and the baseline between Ishioka and Kokee every fourth minute.
The detailed scan sequence is presented in Tab. 1.
We created schedules with regular observations: Ineach minute each station is participating in one quasar
observation. The first 30 s are reserved for the slewingof the telescope and the remaining 30 s are used forthe observation. This is possible because VGOS telescope are very fast, i.e., they can slew to any sourceon the sky within 30 s. Only observations exceeding asignal to noise ratio (SNR) larger than 20 within the
30 s were scheduled. For the SNR computation (e.g.
Gipson 2018) we assumed a VGOS broadband setup
with 32 channels of 32 MHz bandwidth each and 2bit sampling. However, we only used one polariza-

195
Table 1: Overview of the schedule setups. We use the IVS 2-

letter code to identify the stations. A baseline or subnet is agroup of 2-letter codes and different subnets are divided by whitespaces.
scenario scan sequence#obs. #scans #stas. #long bl.
ZT
WnK2 (INT1)
60
60
2
1
WnIs (INT2)
OT
3x WnK2 WsIs
120
120
4
2
3x WnIs WsK2
TT
3x WnOeK2 WsOwIs
1x K2Is WsOw WnOe
315
135
6
4
3x WnOeIs WsOwK2
1x K2Is WsOw WnOetion, leading to a pessimistic SNR compared with the
VGOS setup. Moreover, the antennas of a twin telescope were never observing the same source together.
In fact, the spherical distance between the simultaneously observed sources of a twin station had to belarger than 60◦ . At least 10 minutes had to past until
the same source was observed again by the same station. Moreover, a source could not be observed morethan 6 times by the same observatory (observations ofa twin telescopes are not counted separately).
The optimization criterion for the scheduling is the
local sky coverage. We used the sky coverage score described in Corbin et al. (2019): The hemisphere above
each station is partitioned into cells of equal size andsimilar shape multiple times. If a cell includes an observation its surface area is added to the sky coveragescore. The score is computed for a time period of 10
minutes which is shifted in 5 minutes steps. The partitions are computed following Beckers and Beckers(2012) and have 10, 18, 29 and 107 cells. Twin telescopes were treated as a single telescope for the computation of the sky coverage.
We used an integer linear program (ILP, Williams2013) that incorporates all the constraints explained
above to create the schedules. The ILP is describedin detail in Corbin et al. (2019). However, the ILP weare using in this paper is extended with additional constraints to model the twin stations. Since the observation times and the subnets were predefined (see Tab. 1)
the ILP’s only task was to determine the source thatwas observed by each subnet. With these simplifications it is possible to find the schedule with the optimal sky coverage in a few minutes using a CPU with 2cores at 2,7 GHz.

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Corbin and Haas

3 Simulations
To simulate an observation τsim we computed the geometric delay τg and distorted it with systematic andrandom errors:τsim = τg +clock2 − clock1(1)+M f (2 ) · ZWD2 − M f (1 ) · ZWD1 + wn
For each station i we modeled the clock clocki andthe delay caused by the wet part of the tropospherein zenith direction ZWDi , which was mapped to theelevation i of the observation with a mapping function M f . Here, we used the VMF1 mapping function(Böhm et al., 2006). To each observation, white noisewith a standard deviation of 20 ps was added to simulate random errors.
The geometric delay τg was calculated according
to the IERS conventions (Petit and Luzum, 2010). We
used the ITRF2014 (Altamimi et al., 2016) for station
coordinates and the ICRF2 (Fey et al., 2015) for source
positions. The IERS C04 time series was used for nutation and polar motion. However, we used the BKG eopitime series for UT1, to reduce the interpolation error.
The geometric delay is the only deterministic termin Eq. 1. The other terms are stochastic and require arandom generator for the computation. Each session
was simulated three times, each time with a different
schedule. To avoid different clocks for each simulation of the same session, the station clocks were precomputed and saved. We assumed an Allan standard
deviation of 10 fs at 50 minutes. During the simulation the corresponding clock value was looked up andadded to the delay. With this method, the station clocks
are consistent for each run of the simulation and independent of the schedule.
To make sure that in each simulation of the samesession and station the same troposphere was used, areference troposphere was computed. To do so, thesky above each station was partitioned into 209 cellsof equal size and similar shape using the method fromBeckers and Beckers (2012). For each cell the equivalent zenith wet delay (EZWD) was computed with atemporal resolution of one minute. The EZWDs arecalculated with the turbulence model from Nilsson andHaas (2010) using an initial delay of 450 ps. We used
the turbulence parameters provided in Petrachenko
et al. (2009), except for the station Onsala that is
missing in the list.

During the simulation the EZWD from the cell containing the observation was mapped to the correct elevation and added to the simulated delay. For twin stations the same reference troposphere was used. See
Fig.2 for an illustration of the reference troposphere.
To verify the simulator we simulated the observations of 114 INT sessions in the year 2018. Only sessions with more than 15 good1 observations were used.
Afterwards, the simulated as well as the observed sessions were analyzed using a least-squares adjustment
with standard intensive parametrization2 . For each session we computed the difference in UT1 between thesolution using the simulated observations and the solution using the real observations. The WRMS of thesedifferences is 14 µs which indicates that the simulated
observations are reasonable.

4 Results
The simulated sessions were evaluated with a leastsquares adjustment. Due to the large number of observations (Tab. 1), more parameters can be estimated thanin regular INT sessions. Instead of one ZWD offset weapproximated constant piece wise linear functions (CPWLF) with an interval length of 10 minutes (7 parameters per station). The station clocks were modeled witha CPWLF with 20 minutes interval length (4 parameters per station). The clock at WETTZ13N was fixed.
The target parameter was UT1. We used two different parametrizations for the ZWD for the OT and TT
scenario. In the first setup we estimated a CPWLF foreach antenna. In the second setup we estimated common ZWD parameters for the twin stations. We callthe solutions with combined ZWD parameters OTc andTTc.
We evaluated the different scenarios by comparing
the estimated parameters with the true values. The differences between the estimated and the true value of
UT1 and the ZWD are denoted with UT1 and ZWD ,respectively. For each scenario we calculated the error
in UT1 UT1 in all sessions and computed its mean andthe standard deviation. The results are summarized in
Tab. 2. Using the broadband instead of the legacy S/X
1 vgosDB quality code larger or equal to five
2 The station clock in Wettzell was fixed, the other was estimatedwith a polynom of order two. We estimated one UT1 offset andfor each station a ZWD offset.

Scheduling of Twin Telescopes

197

0 min

2 min

4 min

6 min

8 min

10 min

12 min14 min16 min18 min20 min22 minEZWD [mm]
128

129

130

131

132

133

134

135

136

137

138

Fig. 2: Example of a simulated reference troposphere: Each sky plot represents the troposphere at one point of time. The time

between two subsequent sky plots is two minutes, although the troposphere is computed with a temporal resolution of one minute.
The sky plots are aligned to the north (top of this page) and the center cell corresponds to an elevation of 90 degrees. In this example,
the wind is blowing from north-east direction.

Table 2: Mean and standard deviation of the error in UT1 w.r.t.

Table 3: Mean and standard deviation of the error for the ZWDs

all sessions. The original scenario is a simulation of the schedules that were used for the (observed) INT1 and INT2 sessions
and analyzed with the standard intensive setup.
scenario mean UT1 (µs) std UT1 (µs)
original
−0.5
11.0
ZT
−0.2
8.3
OT
0.4
6.2
OTc
0.5
6.2
TT
0.1
4.2
TTc
0.1
4.2

of each station w.r.t. all sessions. The refractive index structure
constants for the involved stations are give in the last row.
mean ZWD (ps)scenario
Wn
Ws
Kk
Is
On
Os
ZT
−0.06
−0.24 −0.60
OT0.09 0.33 −0.44 −0.15
OTc
0.14−0.53 −0.16
TT−0.30 0.09 −0.53
0.22 −0.21 0.17
TTc
−0.10
−0.57
0.17
0.03

setup (first row vs. second row) the standard deviationof the error in UT1 decreases by almost 3 µs.
With each additional twin telescope the scatter isfurther decreased. In the TT scenario the standard deviation of the error in UT1 is reduced to 4 µs. Combining
ZWD parameters, however, has no significant effect on
the estimation of UT1.
We computed the statistics of the error of the ZWDs
in the same way. The estimated ZWDs were comparedwith the ZWDs in the center cell of the reference troposphere. The results are given in Tab. 3. The standard deviation of the error of the ZWDs decreases slightly byintroducing one twin station (about a half picosecond).
This applies also to the non-twin stations. By estimating common ZWDs parameters the standard deviationis roughly decreased by one picosecond. Furthermore,

ZT
OT
OTc
TT
TTc

std ZWD (ps)
Wn
Ws
Kk
9.3
17.0
8.5
9.0
16.6
8.1
16.6
8.6
8.7
15.0
8.0
15.0

Is
11.9
11.4
11.4
10.3
10.4

On
Os
7.0
6.9
6.1
1

structure constant Cn ( 10−7 m− 3 )
0.94
2.30
1.46
0.72

there is a strong correlation between the standard deviation of the error and the refractive index structure
constant (see last row of Tab. 3).
In case of a rotational symmetric atmosphere the
EZWD is independent of the elevation and the azimuthof the observations. This case is illustrated with a black
dashed line in Fig. 3, which corresponds to the center cell of the reference troposphere. But when consid-

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Corbin and Haas

necessary. Twin stations lead to more observations at
the same observatory, and thus will allow in the futurea more complex troposphere modeling.

140
462
456

136

450

134

444

132

438

130

432

128
20:30

EZWD (ps)

EZWD (mm)

138

426
20:40

20:50

21:00

21:10

21:20

21:30

Fig. 3: Illustration of the reference troposphere at one station for

one session (see Sec. 3 for a description).

ering turbulence, the EZWD depends on azimuth andelevation and cannot be illustrated with a single line
only. Each gray dotted line in Fig. 3 corresponds to the
EZWD in one of the reference troposphere’s cells. The
difference between the true EZWDs (blue diamonds)
and the estimated ZWDs (solid blue line) can reachseveral millimeters. A more sophisticated tropospheremodel appears necessary to model the EZWDs moreaccurately.

5 Conclusions
Introducing VGOS twin stations into INT sessions
leads to more observations with large east-west component, providing improved estimations of the solar
time UT1. Our simulations show that the standard
deviation of the error in UT1 decreases from 11 µs
using the legacy S/X setup to 4 µs using two VGOS
twin stations with a broadband setup. The ZWD estimation is only slightly improved (some picoseconds).
To improve the estimation of the EZWD, a better
troposphere model with more parameters appears

References
Altamimi Z, Rebischung P, Métivier L, et al. (2016) ITRF2014:
A new release of the International Terrestrial Reference
Frame modeling nonlinear station motions. J Geophys Research: Solid Earth, 121(8), 6109–6131
Beckers B, Beckers P (2012) A general rule for disk and hemisphere partition into equal-area cells. Computational Geometry, 45(7), 275–283
Böhm J, Werl B, Schuh H (2006) Troposphere mapping functions for GPS and very long baseline interferometry from
European Centre for Medium-range Weather Forecasts operational analysis data. J Geophys Res, 111, B02406
Corbin A, Niedermann B, Nothnagel A, et al. (2019) VLBI
Scheduling with an Approach from Combinatorial Optimization. submitted to J Geod
Fey A L, Gordon D, Jacobs C S, et al. (2015) The second realization of the international celestial reference frame by very
long baseline interferometry. AJ, 150(2), 1–16
Gipson J (2018) Sked - VLBI Scheduling Software. Technicalreport, NASA Goddard Spaceflight Center
Halsig S, Corbin A, Iddink A, et al. (2017) Current Development
Progress in ivg::ASCOT. A new VLBI Analysis Software.
In: R. Haas, G. Elgered (eds.): Proc. 23rd EVGA Working
Meeting, 167–171
Nilsson T, Haas R (2010) Impact of atmospheric turbulence on
geodetic very long baseline interferometry. J Geophys Res:
Solid Earth, 115(B3)Petit G, Luzum B (2010) IERS Conventions (2010) IERS Technical Note 36, International Earth Rotation and Reference
Systems Service, Verlag des Bundesamtes für Kartographie
und Geodäsie Frankfurt am Main
Petrachenko B, Niell A, Behrend D, et al. (2009) Design Aspects of the VLBI2010 System-Progress Report of the IVS
VLBI2010 Committee. Technical report, NASA Goddard
Space Flight Center
Schnell D (2006) Quality aspects of short duration VLBI observations for UT1 determinations. PhD thesis, Institut fürGeodäsie und Geoinformation, University of Bonn
Williams H P (2013) Model Building in Mathematical Programming, volume 5. John Wiley & Sons.

Comparison of Troposphere Delays from GNSS and VLBI in
R1 and R4 Sessions
V. Puente, Y. Gómez Espada, E. Azcue, S. Garcia-Espada

Abstract This contribution is devoted to the comparison of troposphere Zenith Total Delay (ZTD) derived from the processing of Very Long Baseline Interferometry (VLBI) and Global Navigation Satellite
Systems (GNSS) data in co-located sites. On the one
hand, global and subdaily differences between bothtechniques are analysed in R1 and R4 sessions for theperiod 2013–2018. On the other hand, we use GNSSderived Zenith Wet Delays (ZWD) as a priori value in
VLBI processing, by means of a modified version of
VieVS 3.1. Long-term behaviour of troposphere ties
needed to correct for the height difference between colocated instruments is also studied.

Keywords Troposphere · GNSS · VLBI

1 Introduction
The delay induced by the troposphere in the signal
propagation is an important error source in the analysisof the observations of space geodetic techniques suchas the Global Navigation Satellite Systems (GNSS) andVery Long Baseline Interferometry (VLBI). The magnitude of this delay depends on the atmospheric conditions (temperature, pressure, humidity), the elevationVı́ctor Puente · Yaiza Gómez Espada · Esther Azcue
Instituto Geográfico Nacional
C/General Ibañez de Ibero, Madrid, Spain
Susana Garcia-Espada,Instituto Geográfico Nacional - RAEGE Santa Maria station,
Azores, Portugal(Correspondence: vpuente@fomento.es)

angle of the observation and also on the antenna location.
In this contribution, the differences in the troposphere Zenith Total Delay (ZTD) between both techniques are analysed in several stations in which GNSS
and VLBI antennas are co-located. This analysis has
been carried out using series of troposphere products
from IVS (International VLBI Service for Geodesy andAstrometry, Nothnagel et al., 2017) and IGS (International GNSS Service, Dow et al., 2009). The dataset
analysed corresponds to R1 and R4 sessions spanningfrom 2013 to 2018.
In addition, we have modified VieVS 3.1 to use
GNSS-based ZTD as initial value in VLBI processing.
Results in terms of baselines repeatability are also presented and compared to those obtained with the baseline version of VieVS 3.1. In addition, taking advantage of the computation of troposphere ties needed forthis functionality, we analyse the long-term behaviourof the wet and hydrostatic troposphere ties.
To sum up, the aim of this work is to address thefollowing questions based on the analysis of R1 andR4 sessions for the period 2013–2018:• What are the differences of VLBI-based ZTD withrespect to different solutions of GNSS-based ZTD
in co-located sites?
• Is there any subdaily pattern in the differences between techniques?
• How GNSS-based ZTD used as a priori value impact VLBI estimation?
• What is the long-term behaviour of the wet and hydrostatic troposphere ties?
199

200

2 Resources
The analysis of ZTD is limited to those sites in which
there are VLBI and GNSS antennas co-located. In particular, the ZTD corresponding to the following sites
have been analysed:• Bd (Badary)• Hb (Hobart)• Ke (Katherine)• Kk (Kokee)• Ma (Matera)• Mc (Medicina)• Ny (Ny-Alesund)• On (Onsala)• Ts (Tsukuba)• Wz (Wettzell)• Yg (Yarragadee)• Zc (Zelenchukskaya)

Puente et al.
Table 1: GNSS-VLBI ZTD differences (units: mm).

Solution
CGS
IAA
IVS
VIE
VLBI - GNSS CODE 0.7 ± 7.0 −1.2 ± 7.4 −0.7 ± 7.2 0.8 ± 7.9
VLBI - GNSS IGS
0.5 ± 7.7 −1.3 ± 8.3 −0.9 ± 8.0 0.8 ± 7.9

by the troposphere tie (∆ZTD) using the Brunner andRüeger (1992) formulation. The differences are very
similar between VLBI solutions and no apparent difference can be appreciated in using CODE (network solution technique) or IGS (PPP technique) derived ZTD.
Nonetheless, a subdaily analysis of the differences
has been carried out in order to find a potential bathtube
effect in the differences between techniques, due to thefact that GNSS observation sessions start at 00:00 UTC
and VLBI R1/R4 sessions start at 18:00 UTC. Figure 1 shows the histogram of the differences segmented
by UTC hours for the period analysed (2013–2018) in
Wettzell station when compared to CODE ZTD.

VLBI-based ZTD were retrieved from IVS combination center (Heinkelmann, 2013). Three individual solutions from different software packages and the combined solution were analysed:• CGS (Centro di Geodesia Spaziale), using
Calc/Solve software package.
• IAA (Institute of Applied Astronomy), using
QUASAR software package.
• VIE (TU Wien), using VieVS software package.
• IVS combined solution
Concerning, GNSS-based ZTD, two different solutions
were used:• CODE products (Dach et al., 2018): network solution and ZTD estimated at 2 hours sampling.
• IGS products: Precise Point Positioning (PPP,
Zumberge et al., 1997) and ZTD estimated at
5 min sampling.

Fig. 1: GNSS CODE ZTD - VLBI ZTD at Wettzell.

Figure 2 provides the same histogram but using IGS
ZTD.

3 Results
3.1 GNSS-VLBI ZTD differences
The global differences between GNSS and VLBI derived ZTD are shown in Table 1 separately for each
VLBI and GNSS solution in terms of mean value andstandard deviation, having corrected the differences

Fig. 2: GNSS IGS ZTD - VLBI ZTD at Wettzell.

It seems clear that IGS (PPP) solution has a subdiurnal pattern in the ZTD differences. Similar figures
have been obtained for other stations. Only the ones

Comparison of Troposphere Delays GNSS-VLBI

201– Compute the zenith delay correction due toheight difference ∆ZTD (troposphere tie).
– Compute a priori Zenit Wet Delay (ZWD) as
follows:
ZWD = ZTDGNSS − (ZHDVLBI + ∆ZTD) (1)Fig. 3: GNSS CODE ZTD - VLBI ZTD at Badary.

– Map ZHD and GNSS-derived ZWD to slant
direction using VMF1 (Böhm et al., 2006) andadd gradients contribution.

This rationale is only applied when GNSS data is available. We computed the trospophere ties (∆ZTD) using
the Brunner and Rüeger (1992) formulation, taking atmosphere parameters from the VLBI observation files.

Fig. 4: GNSS IGS ZTD - VLBI ZTD at Badary.

corresponding to Badary site (figures 3 and 4) are included for the sake of brevity. We have tried to correlate this effect to several station displacement effects
without any findings.

3.2 GNSS-based ZTD in VLBI
processing
The other main topic dealt with in this work is the usage of GNSS-based ZTD as a priori value in VLBI processing. With this aim, VieVS 3.1 (Böhm et al., 2018)has been modified to automatically perform the following tasks:

We processed R1 and R4 sessions using the baseline version of VieVS 3.1 and the modified version
to use GNSS-derived ZTD as a priori value. In order to have consistent modelled delays and taking into
consideration that not all VLBI sites have co-located
GNSS antennas, it was needed to model a priori ZWD
using VieVS capability of using the Askne and Nordius(1987) formulation. Figure 5 shows the repeatability
for both solutions, where no significant difference isvisible.
Nevertheless, we consider this analysis was not
representative enough given that not all VLBI sites
have co-located GNSS antennas. Due to this, we carried out the same analysis using CONT17 dataset and
we only processed VLBI data for stations that have
GNSS derived ZWD. Figure 6 shows the repeatability
for CONT17 sessions, using nominal configuration, using ZWD and gradientes from GNSS to compute ZTD
a priori value and fixing ZWD and gradientes from
GNSS, i.e. not estimating the effect of the troposphere.

• Read ZTD and gradients from CODE tropospherefiles (TRO SINEX) for the current and following
day and store the data in an existing VieVS structure.
• Extract GNSS coordinates from SINEX file andadd antenna eccentricity.
• For each observation:– Interpolate linearly GNSS ZTD and gradientsto the VLBI observation epochFig. 5: R1 and R4 repeatability. Period 2013–2018.

202

Puente et al.

Again, we found no improvement when using
GNSS-derived ZTD as a priori value and the results
worsen if we do not estimate troposphere effect.

Fig. 6: CONT17 repeatability for the different configurations

used.

Finally, we analysed the long-term behaviour of
the wet and hydrostatic troposphere ties for the period
2013–2018. Table 2 shows the height difference between the GNSS antenna and the co-located VLBI antenna, and the mean and standard deviation of the wet(∆ZWD) and hydrostatic (∆ZHD) troposphere ties.
Hydrostatic troposphere ties have larger magnitude
but small variation as they mainly depend on the height
difference whereas the wet troposphere ties are almost
negligible, with a mean value below one millimeter andstandard deviation below 0.4 millimeters. These results
are shown graphically in Figure 7.

Table 2: Behaviour of troposphere ties for the period 2013–

2018.
Sites
∆H (m) ∆ZWD (mm) ∆ZHD (mm)Bd-BADG
10.2−0.3 ± 0.2 −2.6 ± 0.2
Hb-HOB2−0.1
0.0 ± 0.0
0.0 ± 0.0
Ke-KAT1
5.0−0.3 ± 0.1 −1.3 ± 0.0
Kk-KOKE
9.2−0.4 ± 0.0 −2.2 ± 0.0
Ma-MATE
7.6−0.3 ± 0.1 −2.0 ± 0.1
Mc-MEDI
17.2−0.8 ± 0.3 −4.7 ± 0.2
Ny-NYAL
3.7−0.1 ± 0.0 −1.1 ± 0.0
Ts-TSKB
17.5
0.9 ± 0.4 −4.8 ± 0.2
On-ONSA
12.8−0.5 ± 0.2 −3.6 ± 0.1
Wz-WTZR
3.1−0.1 ± 0.0 −0.8 ± 0.0
Yg-YAR2
6.9−0.3 ± 0.0 −1.8 ± 0.1
Zc-ZECK
8.8−0.3 ± 0.1 −2.1 ± 0.1

4 Conclusions
The analysis of R1 and R4 sessions for the period
2013–2018 focused on troposphere delays led to thefollowing conclusions:• VLBI-based ZTD show similar level of agreementin terms of mean bias and standard deviation with
CODE and IGS products.
• No subdaily pattern has been appreciated in the
differences with respect to CODE ZTD but there isa subdaily pattern for IGS ZTD whose root cause
has to be further analysed.
• GNSS-based ZTD used as a priori value in VLBI
processing do not improve estimation in terms of
repeatability.
• Long term analysis of troposphere ties shows stable behaviour of wet and hydrostatic ties, withstandard deviation of wet tie below 0.4 mm for theset of stations analysed.

References
Askne J, Nordius H (1987) Estimation of tropospheric delay for
microwaves from surface weather data. Radio Sci., 22, 379–
386
Böhm J, Werl B, Schuh H (2006) Troposphere mapping functions for GPS and Very Long Baseline Interferometry fromeuropean centre for medium-range weather forecasts operational analysis data. J Geophys Res, 111(B02):406,
doi:10.1029/2005JB003629
Böhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry. PASP,
130(986), 044503
Brunner F K, Rüeger J M (1992) Theory of the local scale parameter method for EDM. Bull Géodésique 66:355–364
Dach R, Schaer S, Arnold D, et al. (2018) CODE final productseries for the IGS. Published by Astronomical Institute, University of Bern, http://www.aiub.unibe.ch/download/CODE,
doi:10.7892/boris.75876.3
Dow J M, Neilan R E, Rizos C (2009) The International GNSS
Service in a changing landscape of Global Navigation Satellite Systems. J Geod, 83:191–198, doi:10.1007/s00190-0080300-3
Heinkelmann R (2013) IVS Rapid Troposphere Product – A
Possible Extension Regarding the IGS TWG (C. Hackman).
Presented at the 14th IVS Analysis Workshop, Espoo
Nothnagel A, Artz T, Behrend D, et al. (2017) International
VLBI Service for Geodesy and Astrometry – Deliveringhigh-quality products and embarking on observations of thenext generation. J Geod, 91(7), 711–721

Comparison of Troposphere Delays GNSS-VLBI

203

Fig. 7: Mean and standard deviation of wet and hydrostatic troposphere ties.

Teke K, Böhm J, Nilsson T, et al. (2011) Multi-technique comparison of troposphere zenith delays and gradients during
CONT08. J Geod, 85(7):395–413, doi::10.1007/s00190010-0434-y

Zumberge J F, Heflin M B, Jefferson D C, et al. (1997) Precise
Point Positioning for the Efficient and Robust Analysis of
GPS Data from Large Networks. J Geophys Res, 102 (B3):5005-17

An Assessment of the Tropospheric Parameters EstimatedFrom the CONT17 Campaign
T. Nilsson, K. Balidakis, T. Ning

Abstract We investigate the tropospheric parameters –the Zenith Total delays (ZTD) and horizontal gradients– estimated from the CONT17 VGOS sessions. These
are compared to the results of the CONT17 legacy sessions, from GNSS, and from the ERA5 reanalysis. We
find that the WRMS differences between the ZTD fromthe VGOS sessions and GNSS is on the level of 3–
4 mm, which is similar or even slightly better than what
is obtained from the legacy VLBI data. For the gradients the WRMS differences are about 0.3–0.4 mm,
what is similar to the results from the legacy sessions.

Keywords VLBI · tropophere · GNSS · CONT17 ·ERA5

1 Introduction
The CONT campaigns are continuous 15-day VLBI
campaigns performed approximately every third year
to demonstrate the current state-of-the-art of geodetic
VLBI. The data from the CONT campaigns are often
used in studies to evaluate the performance of VLBI.
For example, the tropospheric delays from VLBI during several CONT campaigns were compared to othertechniques, such as GNSS, DORIS, water vapour raTobias Nilsson · Tong Ning
Lantmäteriet – The Swedish Mapping, Cadastral, and Land Registration Authority, Lantmäterigatan 2C, SE-801 82 Gävle, Sweden
Kyriakos Balidakis
GFZ German Research Centre for Geosciences, Telegrafenberg
A17, DE-14473 Potsdam, Germany(Correspondence: jan-tobias.nilsson@lm.se)

90˚

60˚
30˚

0˚

−30˚

−60˚
−90˚
−180˚ −90˚ 0˚

90˚ 180˚
Fig. 1: Map of the locations of the stations participating in

the CONT17 campaign. The red circles show the stations in
the Legacy 1 network, the green diamonds the stations in the
Legacy 2 network, and the blue stars the VGOS stations.

diometers, and numerical weather prediction models(NWM), in Teke et al. (2013).
The most recent CONT campaign was CONT17,
which was performed from 28 November to 12 December, 2017 (Behrend et al., 2017). Different from the previous CONT campaigns, which only employed a single
station network, there were three independent station
networks observing in parallel in CONT17, see Fig. 1.
There were two networks consisting of legacy VLBI
antennas, called Legacy 1 (14 stations) and Legacy 2(13 stations). In addition, there was a network of six
new VGOS (VLBI Geodetic Observing System) stations observing for five days of the campaign, between
December 3, 23:00 and December 9, 00:00. This is especially interesting since this is the first VGOS data set
being publicly released, thus allowing for a first evaluation of the performance of the new VGOS concept
and comparison with the legacy system.
204

CONT17 Troposphere
Table 1: A list of the VGOS antennas participating in the

CONT17 VGOS test campaign, co-located legacy VLBI telescope participating in one of the legacy CONT17 networks, andthe co-located GNSS antenna used in this work. For each GNSS
antenna, the satellite systems used are also listed (G: GPS, R:
GLONASS, E: Galileo).
VGOS
Legacy 1
Legacy 2
GNSS
WETTZ13S WETTZELL WETTZ13N WTZZ (GRE)
WESTFORD WES2 (GR)GGAO12M GODE (G)ISHIOKA
ISHI (GRE)
KOKEE12M KOKEE
KOKV (GRE)RAEGYEB YEBES40M YEBE (G)In this work we evaluated the tropospheric parameters – the Zenith Total Delays (ZTD) and horizontal
gradients – estimated from the CONT17 VGOS
sessions. This was done by comparing with the resultsfrom the legacy antennas at stations having telescopes
participating in both the CONT17 VGOS network
and a legacy network. In addition, we performed an
external evaluation by comparing with the troposphericparameters estimated from co-located GNSS receivers,
as well as those calculated from the NWM fields fromthe fifth ECMWF reanalysis (ERA5, Copernicus
Climate Change Service (C3S), 2017). The CONT17
VGOS antennas are listed in Table 1, along withthe co-located legacy telescopes and the co-located
GNSS station used in this work. It should be notedthat the VGOS antenna in Yebes, Spain, RAEGYEB,
experienced pointing problems during CONT17, andas a consequence only the data from the first day of thecampaign were found usable.

205

one set of station and radio source coordinates for thewhole campaign. The ZTD and gradients were estimated with temporal resolution of 20 minutes and 2 h,respectively.

2.2 GNSSThe GNSS observations were analysed with theBernese GNSS software version 5.2 (Dach et al.,2015). We applied the Precise Point Positioning (PPP)
strategy, using the final orbits and clock products
provided by CODE (Dach et al., 2018). The satellite
systems used in the analysis are those listed in Table 1.
We first analysed each day individually, then all daysof CONT17 were combined with the ADDNEQ2 module
in order to obtain just one coordinate estimate perstation for the whole period and continuous time seriesof the tropospheric parameter. The parametrisationof the tropospheric delays (temporal resolution andmapping function) was the same as was used in the
VLBI analysis.

2.3 ERA5
Ray-tracing though the ERA5 fields (1 hour temporal
resolution, 31 km spatail resolution) was performed ata number of predefined azimuth and elevation angles.
To these ray-trace delays we then fitted 1st and 2ndorder gradients. For more details, see Zus et al. (2014)
and Balidakis et al. (2018).

2 Data analysis
2.1 VLBIThe VLBI data were analysed with the VieVS@GFZ
software (Nilsson et al., 2015). The a priori modelling
was done according to the IERS 2010 Conventions (Petit and Luzum, 2010) and the parameter estimation was
done with the least squares module of the software.
The Vienna Mapping Functions 1 (VMF1, Böhm et al.,2006) and the gradient mapping function of Chen andHerring (1997) were used. First, each one-day session
was analysed individually, then for each network we
combined all sessions in a global solution, estimating

3 Results
3.1 ZTD
In order to compare ZTD from different techniques, theZTD estimates of all techniques must be reduced to
a common height. This was done by applying tropospheric ties, following the procedure described in Tekeet al. (2013). Given that the height differences between
the co-located instruments were just a few meters at
most, this method should be sufficient.

206

Nilsson et al.
Table 2: Weighted mean and WRMS (in parenthesis) differences

2280
VGOS
Legacy 1
Legacy 2
GNSS WTZZERA5ZTD [mm]

2260
2240
2220
2200
2180
2160
4

5

6

7

8

9

(in mm) between the ZTD estimated from the VGOS antennas and from co-located GNSS antennas, ERA5, and co-locatedlegacy VLBI telescopes.
Antenna
GNSS
ERA5 Legacy 1 Legacy 2
WETTZ13S −0.6 (3.2) −1.9 (5.3) −1.1 (4.5) −2.2 (4.3)
WESTFORD −3.8 (3.5) −1.7 (4.6)––
GGAO12M
3.3 (3.7) −0.1 (3.9)––
ISHIOKA
2.4 (3.7) 0.5 (6.9)––
KOKEE12M −3.9 (5.4) 13.1 (8.3) −4.0 (5.9)–
RAEGYEB
2.4 (3.1) 3.5 (3.8) −0.1 (3.6)–

30

ZTD [mm]

20
10
0
-10

Legacy 1-VGOS
Legacy 2-VGOS
GNSS WTZZ-VGOS
ERA5-VGOS

-20
-30
4

5

6

7

8

9

Day of December 2017

Fig. 2: Top plot shows time series of ZTD estimated at Wettzell

during CONT17 from the VGOS VLBI telescope, the two legacy
VLBI telescopes, the WTZZ GNSS antenna, and from ERA5.
Bottom plot shows the difference between the VGOS time series
and all others.

Figure 2 shows time series of ZTD from theWettzell site in the time period 4-8 December, 2017.
This station had telescopes in all three CONT17 networks: WETTZ13S (VGOS), WETTZELL (Legacy 1),
and WETTZ13N (Legacy 2). The ZTD estimated fromthese three telescopes agree relatively on the level of 4–5 mm. The exception is in the beginning of December
8, where the WETTZ13S ZTD differs from the others
by about 2 cm. Probably the sensitivity of WETTZ13S
was lower during this period, resulting in the rapid
increase in the ZTD not being captured as good as
done by the other telescopes and the other techniques.
The agreement with GNSS is actually slightly better
than with legacy VLBI; the Weighted RMS (WRMS)
difference between the ZTD from WETTZ13S andthe GNSS antenna WTZZ is 3.2 mm. This is slightly
better than for the legacy VLBI telescopes, where the
WRMS difference to GNSS is 3.9 mm. The agreementwith ZTD from ERA5 is worse, the WRMS differenceis 5.3 mm for WETTZ13S, 5.2 mm for WETTZELL,
and 5.4 mm for WETTZ13N.
Table 2 lists the Weighted Mean (WM) and WRMS
of the differences between the ZTD estimated fromthe VGOS telescopes and from GNSS, from ERA5,
and from legacy VLBI. For the case of REAGYEB(Yebes, Spain), it should be noted that the WM and
WRMS values are only based on one day of data (compared to five days for the others), since there were
only useful observations from this antenna for one day.
We can note that the agreement with GNSS is similar or even slightly better than what is usually foundbetween VLBI and GNSS, with a bias of a few mm
and a WRMS difference of 3–4 mm. The exception is
KOKEE12M, where the WRMS difference is 5.4 mm.
This is larger than what is obtained for the legacy antenna KOKEE (legacy 1 network), where the WRMS
difference to GNSS is 4.8 mm. One reason could bethat KOKEE12M had fewer observations comparedto the other VGOS telescopes, on average 350/1000
scans/observations per day. This is much lower thanWETSFORD and GGAO12M, where there were morethan 1000 scans resulting more than 2000 observations
per day. However, for the other VGOS telescopes thenumber of scans/observations were not that different
from KOKEE12M, for example ISHIOKA made about
410 scans and and 1200 observations per day. Hencethe number of scans/observations is probably only partof the reason for the worse results at KOKEE12M.
When comparing to ERA5 the WM and WRMS differences are slightly higher compared to when comparing to the GNSS. Notable is a bias of 1.3 cm at KOKEE12M. Most likely this is an issue with the finite
spatial resolution of the ERA5 orography.

3.2 Gradients
The comparison of the North gradients estimated using
the different techniques at Wettzell is shown in Fig. 3.
As usual when comparing gradients, the agreement be-

CONT17 Troposphere

207
Table 4: Weighted mean and WRMS (in parenthesis) differences

North Grad. [mm]2

VGOS
Legacy 1
Legacy 2
GNSS WTZZ
ERA5

1

0

-1

-2

4

5

6

North Grad. [mm]

1.5

7

8

9

Legacy 1-VGOS
Legacy 2-VGOS
GNSS WTZZ-VGOS
ERA5-VGOS

1
0.5(in mm) between the North gradients estimated from the VGOS
antennas and from co-located GNSS antennas, ERA5, and colocated legacy VLBI telescopes.
Antenna
GNSS
ERA5 Legacy 1 Legacy 2
WETTZ13S 0.0 (0.3) 0.1 (0.3) 0.2 (0.3) 0.0 (0.4)
WESTFORD −0.2 (0.4) 0.1 (0.3)––
GGAO12M
0.1 (0.4) −0.1 (0.2)––
ISHIOKA−0.1 (0.4) −0.2 (0.3)––
KOKEE12M 1.0 (0.7) 0.7 (0.6) 0.6 (0.6)–
RAEGYEB
0.1 (0.3) 0.0 (0.3) 0.1 (0.3)–

seems that the results for this station is a not as good as
for the other VGOS stations, the complete reason needs
further investigations.

0
-0.5
-1
-1.5

4

5

6

7

8

9

Day of December 2017

4 Conclusions and outlook

Fig. 3: Top plot shows time series of North gradients estimatedat Wettzell during CONT17 from the VGOS VLBI telescope,
the two legacy VLBI telescopes, the WTZZ GNSS antenna,and from ERA5. Bottom plot shows the difference between the
VGOS time series and the other ones.

tween the techniques is not as good as in the case of
ZTD. Nevertheless, we find a decent agreement. Especially, we can note that the all techniques see a decreasein the gradient on December 8.
Table 3: Weighted mean and WRMS (in parenthesis) differences(in mm) between the East gradients estimated from the VGOS
antennas and from co-located GNSS antennas, ERA5, and colocated legacy VLBI telescopes.
Antenna
GNSS
ERA5 Legacy 1 Legacy 2
WETTZ13S −0.2 (0.4) −0.1 (0.3) −0.2 (0.4) −0.1 (0.3)
WESTFORD −0.4 (0.3) 0.0 (0.3)––
GGAO12M
0.1 (0.3) 0.0 (0.2)––
ISHIOKA
0.0 (0.4) −0.0 (0.4)––
KOKEE12M 0.5 (0.5) 0.4 (0.5) 0.5 (0.4)–
RAEGYEB
0.3 (0.3) 0.3 (0.3) 0.2 (0.3)–

WM and WRMS differences between the gradients
estimated from the VGOS antennas and the other techniques can be seen in Table 3 (East gradients) and Table 4 (North gradients). In general, the WRMS differences w.r.t. GNSS and ERA5 are on the level iof 0.3–
0.4 mm, except for KOKEE12M where the WRMS differences are higher. As already discussed in Sec. 3.1, it

The results, especially for the ZTD, show that the performance of the VGOS telescopes, in terms of estimating the tropospheric delays, is at least as good asthat of the legacy antennas. However, we could also
identify some potential issues which need further investigations, like the performance of the KOKEE12M
antenna. Furthermore, the goal of VGOS is to obtain
results with a precision about one order of magnitude
better than the legacy VLBI system, which was notachieved in the CONT17 VGOS campaign. Of course,
this campaign was more designed towards showingthat the new system works, rather than demonstrating
its full potential, hence that level of precision cannot
be expected. Thus, the fact that the VGOS telescopes
give similar precision in the tropospheric delays to thelegacy telescope is promising, however, there is still alot of work to do in order to reach the full potential of
VGOS.
Acknowledgements We are grateful to all parties that contributed to the success of the CONT17 campaign, in particular
to the IVS Coordinating Center at NASA Goddard Space
Flight Center (GSFC) for taking the bulk of the organizationalload, to the GSFC VLBI group for preparing the legacy S/X
observing schedules and MIT Haystack Observatory for the
VGOS observing schedules, to the IVS observing stations
at Badary and Zelenchukskaya (both Institute for Applied
Astronomy, IAA, St. Petersburg, Russia), Fortaleza (Rádio
Observatório Espacial do Nordeste, ROEN; Center of Radio
Astronomy and Astrophysics, Engineering School, Mackenzie
Presbyterian University, Sao Paulo and Brazilian Instituto

208

Nacional de Pesquisas Espaciais, INPE, Brazil), GGAO (MIT
Haystack Observatory and NASA GSFC, USA), Hartebeesthoek(Hartebeesthoek Radio Astronomy Observatory, National
Research Foundation, South Africa), the AuScope stationsof Hobart, Katherine, and Yarragadee (Geoscience Australia,
University of Tasmania), Ishioka (Geospatial Information
Authority of Japan), Kashima (National Institute of Information
and Communications Technology, Japan), Kokee Park (U.S.
Naval Observatory and NASA GSFC, USA), Matera (Agencia
Spatiale Italiana, Italy), Medicina (Istituto di Radioastronomia,
Italy), Ny Ålesund (Kartverket, Norway), Onsala (Onsala Space
Observatory, Chalmers University of Technology, Sweden),
Seshan (Shanghai Astronomical Observatory, China), Warkworth (Auckland University of Technology, New Zealand),Westford (MIT Haystack Observatory), Wettzell (Bundesamt
für Kartographie und Geodäsie and Technische Universität
München, Germany), and Yebes (Instituto Geográfico Nacional,
Spain) plus the Very Long Baseline Array (VLBA) stationsof the Long Baseline Observatory (LBO) for carrying out theobservations under the US Naval Observatory’s time allocation,
to the staff at the MPIfR/BKG correlator center, the VLBA
correlator at Socorro, and the MIT Haystack Observatory
correlator for performing the correlations and the fringe fittingof the data, and to the IVS Data Centers at BKG (Leipzig,
Germany), Observatoire de Paris (France), and NASA CDDIS(Greenbelt, MD, USA) for the central data holds.Furthermore,
we are grateful to the IGS (Dow et al., 2009) for providing the
GNSS data and to ECMWF for the ERA5 data.

References
Balidakis K, Nilsson T, Zus F, et al. (2018)
Estimating integrated water vapour trends from VLBI, GNSS
and numerical weather models: sensitivity to troposphericparameterization. J Geophys Res, 123(12):6356–6372,
doi:10.1029/2017JD028049
Behrend D, Thomas C, Gipson J, et al. (2017) Planning of thecontinuous VLBI campaign 2017 (CONT17). In R. Haas,

Nilsson et al.

G. Elgered (eds.): Proc. 23rd EVGA Working Meeting, 132–
135
Böhm J, Werl B, Schuh H (2006) Troposphere mapping
functions for GPS and very long baseline interferometry
from european centre for medium-range weather forecasts
operational analysis data. J Geophys Res, 111:B02406,
doi:10.1029/2005JB003629
Chen G, Herring T H (1997) Effects of atmospheric azimuthal
asymmetry on the analysis of space geodetic data. J Geophys Res, 102(B9):20489–20502, doi:10.1029/97JB01739
Copernicus Climate Change Service (C3S) (2017) ERA5: Fifth
generation of ECMWF atmospheric reanalyses of the global
climate. Technical report, Copernicus Climate Change Service Climate Data Store (CDS), URL https://cds.climate.
copernicus.eu/cdsapp{#}!/home. Accessed 14 June, 2019
Dach R, Lutz S, Walser P, et al. (eds.) (2015) Bernese
GPS Software Version 5.2 User Manual. Astronomical Institute, University of Bern, Bern Open Publishing,doi:10.7892/boris.72297
Dach R, Schaer S, Arnold D, et al. (2018) CODE final productseries for the IGS. Technical report, Astronomical Institute,
University of Bern.
Dow J-M, Neilan R E, Rizos C (2009) The international GNSS
service in a changing landscape of global navigation satellite systems. J Geod, 83:191–198, doi:10.1007/s00190-0080300-3
Nilsson T, Soja B, Karbon M, et al. (2015) Application of
Kalman filtering in VLBI data analysis. Earth Planets
Space, 67(136):1–9, doi:10.1186/s40623-015-0307-y
G. Petit, B. Luzum (eds.) (2010) IERS Conventions (2010). IERS
Technical Note 36. Verlag des Bundesamts für Kartographie
und Geodäsie, Frankfurt am Main, Germany
Teke K, Nilsson T, Böhm B, et al. (2013) Troposphere delays from space geodetic techniques, water vapor radiometers, and numerical weather models over a series of continuous VLBI campaigns. J Geod, 87(10-12):981–1001,
doi:10.1007/s00190-013-0662-z
Zus F, Dick G, Douša J, et al. (2014) The rapid and precise
computation of GPS slant total delays and mapping factors
utilizing a numerical weather model. Radio Sci, 49(3):207–
216, doi:10.1002/2013RS005280

Time Stability of the K-band Catalog Sources
K. Le Bail, A. de Witt, C. S. Jacobs, D. Gordon

Abstract The ICRF3 was adopted by the IAU in
August 2018 and became effective January 1, 2019.
It differs from ICRF and ICRF2 by the addition of
two catalogs at higher frequencies, including a K-band(24 Ghz) catalog. The K-band data differs from the S/Xdata in different aspects that question if it may be possible to construct a more stable frame at K-band thanat S/X band. We studied two source position time series solutions generated at GSFC using Calc/Solve: one
obtained from K-band observations and one from S/X
observations. Using the Allan variance, we determined
their noise floor. Since the two source position time series solutions present very different sampling, we did
three different comparisons: first we compared the two
sets of time series using all the data as two independent
solutions, then we limited the study to a common time
period, and finally we compared the noise floor of thetwo catalogs on comparable sessions using the VLBA
on a common period. The last comparison shows Kband has a comparable level of noise floor as S/X.

1 Introduction

Keywords Celestial Reference Frame · ICRF · Quasar· K-band · Noise floor · Allan variance

Table 1: Statistics on GSFC K-band and S/X-band catalogs pro-

Karine Le Bail · David Gordon
NVI, Inc., Greenbelt, MD, U.-S.

The ICRF3 is composed of catalogs at three frequencies. In this paper we examine the relative temporalstability of two of those, S/X and K bands.
The K-band data differs from the S/X data in that
1) the K-band in the north is VLBA-only; 2) the Kband data since 2015 are all at a high data rate of
2 Gbps; and 3) K-band is less affected by source structure. Thus it may be possible to construct a more stable
frame at K-band than at S/X band (see de Witt et al.
(2019) for more details on the K-band Celestial Reference Frame).
The two source position time series solutions westudied were generated at GSFC using Calc/Solve.
These two solutions present very different sampling.
The K-band observations cover the period May 2002
to November 2018 for a total of 65 sessions while
the S/X observations cover the period August 1979 toJanuary 2019 for a total of 6271 sessions (see Table 1).

cessed in January 2019.
K solution S/X solution
Jan 2019
Jan 2019
Source number
906
4775
Session number
65
6271
First epoch
May 2002 Aug. 1979
Last epoch
Nov. 2018
Jan. 2019
Source number ( > 10 sessions)
354
788

Aletha de Witt
SARAO/HartRAO, Krugersdorp, South Africa
Christopher S. Jacobs
Jet Propulsion Laboratory, California Inst. Technology/NASA,
Pasadena, CA, U.-S.
(Correspondence: karine.lebail@nasa.gov)

In this paper, we compared the two source position
time series solutions on three different configurationsof common source sets depending on observation periods and session types (see summary in Table 2):
209

210
S/X Standard dev:1.512

1. We consider the individual noise floor of the two
independent solutions: we compute the source
noise floor on the entire observation period foreach of the 310 common sources observed in ten
sessions or more of the two catalogs.
2. We focus on the same period of observation for
the two solutions: we compute the source noise
floor on the observation period November 2016
to November 2018 for each of the 87 common
sources observed in ten sessions or more of the twocatalogs.
3. We restrict the study to equivalent sessions: wecompute the source noise floor for each of the 31
common sources observed in ten sessions or morein the 24-hour VLBA sessions (code UD for the
K-band and codes UF/UG for the S/X bands) over
the observation period November 2016 to November 2018.

Table 2: Three different configurations studied in this paper.

Observation
periodSession Source
type number

Config. 1
ALL avail. ALL avail.
Config. 2 Nov. 2016 - Nov. 2018 ALL avail.
Config. 3 Nov. 2016 - Nov. 2018
VLBA

310
87
31

Figure 1 gives an example of right ascension position time series for the source 0552+398 for each of
the configurations.
In the second section of this paper, we briefly describe the method we used. The third section presents
the results for the three configurations. The last section
concludes our study.

2 Method
We could study these time series by using the standard
deviation, but this quantity does not take into accountthe evolution of the position with time. So we choose to
use the Allan variance instead and determine the noise
floor using a method presented in Le Bail et al. (2017).
The Allan variance is a statistical tool that gives thelevel and type of noise of a time series. For more details, the reader can refer to previous work in Le Bailand Gordon (2010) or from Allan (1966). The major
drawback of this statistical tool when applied to VLBILe Bail et al.

RAcosDEC (mas)0552+398

K Standard dev: 0.139

RAcosDEC (mas)
1995
2000
2005
0552+398

2010
2015
K Standard dev:

1
0.5

S/X
K

0
−0.5
−1
1980
1985
1990
S/X Standard dev:
0.347
1
S/X
0.5
K
S/X Standard dev:1.864
01
S/X
−0.5
0.5
K

DEC (mas)
0552+398

K Standard dev: 0.165

RAcosDEC(mas)
20182018.52019
K Standard dev:
0552+398
DEC (mas)
2000
2005
2010
2015
K Standard dev:
0552+398−10
2016.520172017.5
S/X Standard dev:
0.214
−0.5
1
S/X
−1
0.5 1980
K 1985
1990
1995
S/X Standard dev:
0.693
01
S/X
0.5
K
−0.5

−10
2016.5−0.5

2017

2017.5

2018

2020
0.158

2018.520192019.5
0.150

2020
0.205

2019.5

Fig. 1: Right Ascension time series for source 0552+398. The

DEC (mas)−1

2016.5 points2017
2017.5to the S/X2018 solution,
2018.5 the black
2019 points
2019.5
bluecorrespondto
S/X Standard dev:
0.209
K Standard dev:
0.209
0552+398
1 K-band solution. Top plot: entire period (configuration 1).
theS/X
Middleplot:
period November 2016 to November 2018 (con0.5
K
figuration
2).
Bottom plot: VLBA sessions between November02016 and November 2018 (configuration 3).
−0.5−1
2016.520172017.520182018.520192019.5

position time series is that it has to be applied to regularly spaced time series. As with any other statisticaltool, the significance of the results depends greatly on
the number of points of the time series.
The observed VLBI data presents challenges forthis statistical tool: there may be some large gaps between observations, the sessions may be scarce and/or
the number of observations is limited. For these reasons, we chose to perform monthly and yearly averaging of the time series. If the time series has a large gap
or too many missing points, the time series is not considered in the study.
The different steps of the method are describedhereafter:
1. Keep sources with ten or more observations to increase the significance of the statistics;
2. Monthly and yearly averages and interpolation toregularize our time series;
3. Allan variance processing for each source, eachcoordinate, each solution;
4. Noise floor determination for each source and eachcoordinate. If the noise type determined by theslope of the Allan variance curve (see Figure 2)
is white or flicker, the noise floor is the lowest Allan variance. If the noise type is random walk, thenoise floor is undefined.

Figure 1. Position time series of 3C418 (middle plots), Allan
variances computed from 1989-1993 time series (left plots) andAllan variances computed from 1997 to 2014.1 time series (rightplots).
Source noise floor (µas)

211

Flickernoise

Source noise floor (µas)

60
Source noise floor (µas)

Source noise floor (µas)

RAcos(DEC) ! K!band

40
30
20

S/X noise floor
K noise floor

400
300
200
100
0

!80

!60

!40

!20

0

20

40

60

80

DEC

Figure 2. The Allan variance to determine the type of noi

Fig. 2: Allan variance. Determination of noise scheme.

50

500

Declination (deg)log10 !

60

RAcos(DEC)Reminder: The Allan variance is a statistical tool used t
type and level of noise of stationary time series by compvariance over various sampling time !. The slope of thecurve indicates the type of noise as illustrated in Figure 2

R
an
w dom
al
k

te
hi e
W ois
n

log10(Allan var.)

Time Stability of K-band Sources

DEC ! K!band

50

500

S/X noise floor
K noise floor

400
300
200
100
0

!80

References
!60

!40

!20

0

20

40

60

80

Declination (deg)Fig. 4: Noise floor comparison in 10◦ declination bands. Config-

40
30
20

uration 1: entire observation period – 310 common sources. Top
plot: right ascension component, bottom pot: declination component.

[1] Feissel-Vernier, M., Selecting stable extragalactic compact radio sources fromastrogeodetic
VLBI program,
A&A, 2003.
RAcos(DEC) ! S/X!band
DEC ! S/X!band
10

0

100

200

300

400

0

500

100

200

300

400

500

60

Source noise floor (µas)

60

Source noise floor (µas)

10

50

50

most of the sourcesSelection
have a noiseof
floor
than
[2] Le Bail, K., and D. Gordon, Time-dependent
anlower
OptimalSet of Sou
200 µas for the right ascension component and it isStable Celestial Reference, in Proceedingsof the IVS 2010 General Meeting, Hoba
more scattered for the declination component with anoisefloor averagearound 200 µas.
7-13, 2010, Eds D. Behrend and K. D.
Baver,
p.280–284.
40
30
20
10

0

100

200

300

400

500

40
30
20
10

0

100

200

300

400

500

Fig. 3: Noise floor determined by the Allan variance. Configu-

Figure 4 presents the same results averaged overration 1: entire observation period - 310 common sources. Top 10◦ declination bands. For declination bands higher
plots: K-band solution, bottom plots: S/X solution. Right plots: than −20◦ , the noise floors for the S/X solution is visiright ascension component, left plots: declination component.
bly larger
thanNetwork
for the K solution.
8th IVS General Meeting – VGOS: The New
VLBI

3 Results

This seems to indicate that the K noise floor tends
to be smaller than the S/X noise floor when we consider
the two solutions on their entire period.

3.1 Configuration 1: entire observation
period – 310 common sources

3.2 Configuration 2: Nov. 2016–Nov.
2018 observation period – 87
The K solution contains 65 sessions over its entire pecommon sources
riod of observation (May 2002 to November 2019) andthe S/X solution contains 6271 sessions (August 1979
to January 2019). There are 310 common sources thatwere observed in ten or more sessions.
We compute the noise floor for each of these 310
sources, for each component and each solution. The
results are displayed in Figure 3 as individual source
noise floor histograms and in Figure 4 as noise floor
averages on 10◦ declination bands.
As seen in Figure 3, most of the sources in the
K-band solution have a source noise floor lower than
80 µas for the right ascension component and 100 µas
for the declination component. For the S/X solution,

The VLBI technique has seen significant improvements and the quality of the data improved with time.
The previous comparison is biased since the S/Xsolution contains all the data from the beginning of
VLBI when the quality of the data was not as goodas it is currently. In this section, the comparison isdone on the common period of observation for the twosolutions: November 2016 to November 2018, for a
total of 44 sessions for the K solution and 391 sessions
for the S/X solution. The common sources that wereobserved in ten or more sessions are 87 sources.

212

200

300

400

RAcos(DEC) − S/X−band

15
10
5
0

100

200

300

400

10
5

100

300

400

5

500

DEC − S/X−band

20

15

15
10
5

100

200

300

400

500

100

200

300

400

RAcos(DEC) − S/X−band

5

100

200

300

400

500

DEC − K−band

10

5

0

500

10

0

0

500

200

15

10

0

0

500

Source noise floor (µas)

Source noise floor (µas)

20

100

15

RAcos(DEC) − K−bandSource noise floor (µas)

5Source noise floor (µas)

1015Source noise floor (µas)

150DEC − K−band20

15
Source noise floor (µas)

RAcos(DEC) − K−bandSource noise floor (µas)

Source noise floor (µas)

20

Le Bail et al.

100

200

300

400

500

DEC − S/X−band

10

5

0

100

200

300

400

500

Fig. 7: Noise floor determined by the Allan variance. Configura-tion 2: Nov. 2016–Nov. 2018 – 87 common sources. Top plots:
K-band solution, bottom plots: S/X solution. Right plots: rightascension component, left plots: declination component.

tion 3: Nov. 2016–Nov. 2018 and VLBA sessions – 31 common
sources. Top plots: K-band solution, bottom plots: S/X solution.
Right plots: right ascension component, left plots: declination
component.

Source noise floor (µas)

Fig. 5: Noise floor determined by the Allan variance. Configura-RAcos(DEC)500
S/X noise floor
K noise floor

400
300
200
100
0

−80

−60

−40

−20

0

20

40

60

80

Source noise floor (µas)

Declination (deg)DEC
500
S/X noise floor
K noise floor

400
300
200
100
0

−80

−60

−40

−20

0

20

40

60

80

Declination (deg)Fig. 6: Noise floor comparison in 10◦ declination bands. Config-

uration 2: Nov. 2016–Nov. 2018 – 87 common sources. Top plot:right ascension component, bottom pot: declination component.

The results are displayed in figures 5 and 6. Contrary to the previous configuration, the S/X noise floor
tends to be smaller than the K noise floor in both figures.

3.3 Configuration 3: Nov. 2016–Nov.
2018 observation period of VLBA
sessions – 31 common sources
The configuration 2 study could also be consideredbiased since we compared 44 sessions for the K solution to 391 for the S/X solution, all 391 sessions

with different observation settings and quality. In thisthird part, we compared only on the common period(November 2016 to November 2018) for similar sessions. In this case, we consider the data from 40 24hour VLBA sessions at S/X band, called UF001 and
UG002 sessions, and 27 24-hour VLBA sessions at Kband, called UD sessions. The VLBA sessions at S/Xband observed 4145 sources in a very small number ofsessions while the VLBA sessions at K band observed
819 sources. The reason for the source number discrepancy is mostly explained by the goals of the VLBA sessions at S/X band. The goals were mostly to improve
the precision of ICRF3, as well as for ICRF3 maintenance. So approximately 3300 of the weakest ICRF3
sources were re-observed during these sessions. Thereare 31 sources observed in ten or more observations
that are common in the two subsets of the solutions.
The results are in figures 7 and 8. In Figure 7 forthe right ascension component, most of the sources in
the K band solution have a source noise floor lower
than 100 µas while most of the sources in the S/X solution have a source noise floor lower than 150 µas.
This is less significant for the declination component
even though the distribution is more scattered for the
S/X solution. When comparing on declination bands in
Figure 8, the two solution noise floors are within theerror bar for the declination bands higher than −30◦ .
In conclusion the K noise floor tends to be comparable to the S/X noise floor when considering similar
sessions and a similar observing period.

Source noise floor (µas)

Time Stability of K-band Sources

213

RAcos(DEC)500
S/X noise floor
K noise floor

400

by AuScope Ltd., funded under the National Collaborative
Research Infrastructure Strategy (NCRIS).

300
200

References

100
0

−80

−60

−40

−20

0

20

40

60

80

Source noise floor (µas)

Declination (deg)DEC
500
S/X noise floor
K noise floor

400
300
200
100
0

−80

−60

−40

−20

0

20

40

60

80

Declination (deg)Fig. 8: Noise floor comparison in 10◦ declination bands. Config-

uration 3: Nov. 2016–Nov. 2018 and VLBA sessions – 31 common sources. Top plot: right ascension component, bottom pot:
declination component.

4 Conclusions and outlook
The K-band observations have reached a level of stability equivalent to the level of current S/X observations. They benefited from the history of the S/X observations. The strength of the S/X data set is in its
broad diversity of baselines and sessions. Comparing
the VLBA sessions UD (K-band) and UF-UG (S/X),
it seems to show that the K-band statistical stability is
better than the S/X-band statistical stability. We needmore K-band observations to continue monitoring andcomparing the stability of the frame realized by the Kband observations.
Thanks to the VLBA, K-band observations have increased greatly in the past two years, prompting manystudies as demonstrated by the four papers presented at
the EVGA 2019.
Acknowledgements Copyright ©2019. All Rights Reserved.
U.S. Government sponsorship acknowledged for work done at
JPL-Caltech under a contract with NASA.
The VLBA is managed by NRAO, funded by the National
Science Foundation, and operated under cooperative agreement
by Associated Universities. The authors gratefully acknowledge
use of the VLBA under the USNO’s time allocation. This work
supports USNO’s ongoing research into the celestial reference
frame and geodesy.
HartRAO is a facility of the National Research Foundation(NRF) of South Africa. The Hobart telescope is operated by the
University of Tasmania and this research has been supported

Allan D (1966) Statistics of Atomic Frequency Standards.
Proc IEEE, 54(2):221–230
de Witt A, Gordon D, Jacobs C S, et al. (2019) The Kband (24 GHz) 2019a Celestial Reference Frame. Poster
at the 24th EVGA Working Meeting, http://www.oan.es/
evga2019/EVGA2019 PDF/P306 EVGA2019 deWitt.pdf
Krásná H, Gordon D, de Witt A, et al. (2019) Earth Orientation
Parameters estimated from K-band VLBA measurements.
In: R. Haas, S. Garcia-Espada, J. A. López Fernández (eds.),
Proc. 24th EVGA Working Meeting, 238–242
Le Bail K, Gordon D (2010) Time-dependent Selection of an Optimal Set of Sources to Define a Stable Celestial Reference
Frame. In: D. Behrend, K. Baver (eds.): IVS 2010 General
Meeting Proceedings, NASA/CP-2010-215864, 280–284
Le Bail K, Gordon D, Gipson J M, et al. (2017) Investigating thenoise floor of VLBI source positions. In: R. Haas, G. Elgered(eds.): Proc. 23rd EVGA Working Meeting, 186–189
Soja B, Jacobs C S, Runge T, et al. (2019) Ionospheric calibration for K-band celestial reference frames. Presentation at the 24th EVGA Working Meeting, http://www.oan.
es/evga2019/EVGA2019 PDF/O316 EVGA2019 Soja.pdf

VLBA Imaging of ICRF 3 Sources
L. Hunt, M. Johnson, A. Fey, J. Spitzak, D. Gordon

Abstract We present results from a Very Long Baseline Array (VLBA) imaging campaign of sources included in the third realization of the International Celestial Reference Frame (ICRF). Imaging these sources
allows us to determine spectral index, peak flux density, compactness and source structure index. This information is crucial to understanding source structure
and variability which better allows us to determine if asource is suitable for inclusion in the ICRF and suitable
as a phase reference calibrator. We also describe where
the images and ancillary data will be publicly available
in the future.

Keywords ICRF · Imaging · VLBA

1 Introduction
The International Celestial Reference Frame is comprised of positions of compact quasars calculated from
Very Long Baseline Interferometry (VLBI) observations at 2.3 GHz and 8.4 GHz. It has now been throughthree full realizations (Hereafter ICRF1, ICRF2, andICRF3) (Ma et al. (1998); Fey et al. (1998); Charlot etLucas Hunt · Megan Johnson · Alan Fey
The United States Naval Observatory, 3450 Massachusetts Ave
NW, Washington, D.C. 20392, United States
John Spitzak
Computational Physics, Inc. 8001 Braddock Road, Suite 210
Springfield, VA 22151-2110, United StatesDavid Gordon
NVI Inc. 7257D Hanover Parkway Greenbelt, MD 20770,
United States(Correspondence: lucas.hunt@navy.mil)

al. in progress). The third realization (ICRF3; Charlot
et al. in progress) was recently adopted by the International Astronomical Union at the most recent general
assembly as the standard reference frame.
ICRF1 (Ma et al., 1998) contained precise postionsof 608 total sources from Very Long Baseline Interferometry observations between 1979 and 1995, with
212 of those sources being defining sources. The second realization of the ICRF (ICRF2, Fey et al., 1998)
built on ICRF1 and included positions of 3,414 totalsources with an updated list of 295 defining sources selected for their positional stability and to be as uniform
as possible across the celestial sphere. ICRF3 includes
positions of 4,536 sources calculated at multiple wavelengths, and an updated list of 303 defining sources.
Sources included in the ICRF are typically distant,compact radio loud quasars. It is important for an inertial reference frame that the sources used to makethat reference frame are distant to minimize the corrections required for proper motion. It is also easier to
get accurate positions from compact sources, and thebrighter they appear at radio wavelengths, the easier it
is to get an accurate position over a short integration.
Bright sources are also easier to monitor for changes instructure which can affect the position measurement.
Campaigns to monitor these changes have been carriedout since 1995.
Many sources included in ICRF2 came from the
Very Long Baseline Array (VLBA) Calibrator Survey(VCS, Beasley et al., 2002; Gordon et al., 2016) observations. The survey was designed to identify a large
number of phase calibrators that can be used to calibrate future VLBA observations. Since the VCS wasa source finding survey, most sources were observed asmall number of times. The VCS added a large numberof positions to the ICRF, but the small number of obser214

Imaging ICRF 3

2 Method
2.1 Observing setup
Data used for this report were obtained in 20 total observation sessions carried out at approximately twice amonth between January 2017 to December 2017. Eachobservation session lasted 24 hours and observed approximately 280 sources with 3,628 total sources being
observed over 12 months. The schedule was designed
to do both astrometry and imaging, covering large portions of the sky and observing most sources multiple
times in each session. This provided for a good mapof the sky during each session and improved the UV
coverage of the telescope to improve the imaging.
The observations were carried out at 2.3 GHz and
8.7 GHz simultaneously. These frequencies allow for
accurate calibration of the Earth’s ionosphere andallow for estimates of the spectral index of observed
sources. The observations used 16 total sub-bands,
four at 2.3 GHz and 12 at 8.7 GHz, with a 32 MHz
bandwidth and 64 channels per sub-band. Observations were done with Right Circular Polarization only
due to data transfer speed limits.

2.2 Calibration and Imaging
Calibration was done using the Astronomical Image
Processing System (AIPS) (Wells, 1985) package. A
basic calibration procedure was designed which makes
corrections to digital correlator offsets, calibrates theamplitude, and corrects the phase. The full data set
is then split into individual source files and written to
disk.
The individual source files are then imported into
the Difmap software package (Shepherd et al., 1994) tocreate the images. The images are created with an automated script that uses the clean algorithm (Högbom,
1974) and self-calibration to improve the quality of theimage. At this point the images are inspected and any
bad data points are removed. The imaging script is thenrun again to create a final image.

3 Results
We observed 3,628 sources over the 20 observations.
Figure 1 shows nearly 3,000 sources were observed
only once over the course of the year and only one
source was included in every observation. Stronger
sources with well-constrained positions were included
in many observations to anchor the observations. The
positions of these sources improved the overall accuracy of ICRF3 and the images will help us determine
source structure corrections for the positions of all objects.
We were able to make images for ≈93 % of thesources at 8.7 GHz and ≈96 % of sources at 2.3 GHz. It
is important to note that of the sources we created im-

103
log(Number of Sources)

vations made positional uncertainties relatively large
compared to more frequently observed sources.
In 2016, the United States Naval Observatory(USNO) entered an agreement with the Long Baseline
Observatory to contribute 50 % of the budget required
to operate the VLBA in order to use 50 % of the time
available for observation. With that time, USNO andthe National Aeronautics and Space Administration
Goddard Space Flight Center (NASA GSFC) havecarried out a monitoring campaign of ICRF3 sourcesin order to get more accurate positions for many of thesources whose positions had only been measured once,
and to image those sources to determine source structure and how that may impact the sources position. We
also plan to make the calibrated data and the images
publicly available for the astronomical and geodetic
community to use. For example they could be used tocorrect source position, or find nearby calibrators forother astronomical studies.
This conference proceeding will discuss the imaging of the aforementioned monitoring campaign, anddescribe how the data will be accessible in the future.

215

102

101

100
0

5

10

15

20

Number of times source was observed

Fig. 1: This plot shows how often sources were visited over 20

observations

216

ages for, approximately 3 % of the images from eachobservation did not have enough data to create a highquality image. After the images are manually inspected
and unreliable images are removed, the percentage ofimages created from each observation will likely belower. Images of a selection of sources representing thevariety in source shape and structure found in these observations can be seen in figures 2 and 3. There are also
a number of observations that did not produce an image of the source likely due to very short observations
that do not produce enough data to make an image. We
have carried out longer observations of a small subsetof sources that we were unable to image in this monitoring campaign in hopes of determining what caused
the initial imaging failure. Calibration and imaging ofdata from these observations is currently underway.
USNO is responsible for preparing images ofsources included in the ICRF. Traditionally we havemade those images publicly available to the astronomical and geodetic communities through the Radio
Reference Frame Image Database. We would liketo announce that we are upgrading that website andchanging the name to the Fundamental Reference
Image Data Archive (FRIDA). The upgraded FRIDA
website will include data from additional experiments
including geodetic RDV experiments, and USNO
VLBA survey experiments. The available images willgo back to observations included in ICRF1 and include
images of sources from S-band through Ka-band. The
upgraded website will include data on each source
including contour plots of the source, the calibrated
data sets, and log files to show how the imaging wasprocessed. The site will allow users to find sources
based on specific search criteria, and download thedata that might be useful to their research. We hope tomake this available within the next year.

4 Conclusions and outlook
USNO has used time on the VLBA to monitor sources
whose positions are included in ICRF3. The monitoring campaign has allowed us to make over 9,000 images of 3,628 sources and we will provide these to theastronomical and geodetic communities. We will makethe images, calibrated data, and log files available on an
updated, user friendly website to be known as FRIDA.

Hunt et al.

In the future, we plan to include the spectral index,
the source structure index, and correction maps of eachsource in each observation within FRIDA. We also intend to update our calibration and imaging process toimprove the reliability of our images while reducing
the amount of manual input required to create a large
number of images. We are also working towards implementing newer software that is more likely to be maintained in the future and add tools as needed to makecalibration and imaging easier. Finally, we also plan tocontinue imaging the USNO monitoring experiments
and to make that data publicly available as close to theobservations as possible.

References
Beasley A J, Gordon D, Peck A B, et al. (2002)
The
VLBA Calibrator Survey – VCS1. ApJS, 141, 13–21,
doi:10.1086/339806
Fey A L, Gordon D, Jacobs C S, et al. (2015) The second realization of the international celestial reference frame by very
long baseline interferometry. AJ, 150(2), doi:10.1088/00046256/150/2/58
Gordon D, Jacobs C, Beasley A, et al. (2016) Second epoch
VLBA calibrator survey observations: VCS-II. AJ, 151(6),154, doi:10.3847/0004-6256/151/6/154
Ma C, Arias E F, Eubanks T M, et al. (1998) The International
Celestial Reference Frame as Realized by Very Long Baseline Interferometry. AJ, 1, 516–546, doi:10.1086/300408
Högbom J A (1974) Aperture Synthesis with a Non-Regular
Distribution of Interferometer Baselines. A&A, 15, 417
Shepherd M C, Pearson T J, Taylor G B (1994) DIFMAP: aninteractive program for synthesis imaging. Bull. Am. Astron.
Soc., 26(2), 987–989
Wells D C (1985) NRAO’S Astronomical Image Processing System (AIPS). In: V. Di Gesù, L. Scarsi, P. Crane, J. H. Friedman, S. Levialdi (eds.) Data Analysis in Astronomy, Ettore Majorana International Science Series, vol 24. Springer,
Boston, MA, 195–209, doi:10.1007/978-1-4615-9433-8 18

Imaging ICRF 3

217

Fig. 2: Examples of images created from our observations displaying the variety in source structure. Images are of the same sourceat both 8.6 GHz and 2.3 GHz

218

Hunt et al.

Fig. 3: Examples of images created from our observations displaying the variety in source structure. Images are of the same sourceat both 8.6 GHz and 2.3 GHz

The Second Version of the Bordeaux VLBI Image Database(BVID)
A. Collioud, P. Charlot

Abstract A new version of the Bordeaux VLBI Image
Database (BVID) is now available online at the following address: http://bvid.astrophy.u-bordeaux.fr.
This second version, with more than 6000 VLBI images and associated data (especially those that qualify
the source structure, i.e. compactness and structure index information) has an enhanced clean and modern
interface. New tools and functionalities are available
to explore the database. Using these, we discuss theflux density and structure index distributions for theapproximately 1300 ICRF3 sources comprised in the
BVID.

Keywords Radiosource · Image · Database · Source
structure · Reference frame

1 Context
The current Celestial Reference Frame, i.e. the ICRF3,
is based on the VLBI positions of 4536 extragalactic radio sources, including 303 defining sources. The
source position accuracy depends on a certain extent
on the compactness of the sources: sources with pointlike structure are more suited for building such reference frame. Unfortunately, most of the sources exhibit non point-like structures on VLBI scales (Fey andCharlot, 1997). In addition, those structures are fre-quency dependent and can also fluctuate over time. Assessing the source compactness and its evolution overtime thus requires to monitor and image the sources
on a regular basis. The International VLBI Service
for Geodesy and Astrometry (IVS) organizes observing sessions adapted to such purpose: these are the bimonthly “Research and Development with the VLBA”(RDV) sessions conducted since 1997 using a global
VLBI network with the 10 VLBA stations and up to 10
other IVS stations.
The Laboratoire d’Astrophysique de Bordeaux,
as an IVS Analysis Center, processes RDV sessions
to produce images of the reference frame sources, inorder to assess their structure. Such images, alongwith additional products (structure correction maps,
visibility maps, flux density values, etc.), are provided
to the community through the Bordeaux VLBI Image
Database (BVID). Besides astrometric applications,
the BVID images are also useful for astrophysicalstudies, i.e. for investigating source morphology
and superluminal motions in those extragalactic
radio sources. The BVID is complementary to theRadio Reference Frame Image Database (RRFID)1
maintained at the United States Naval Observatory(USNO).
Section 2 presents details about the new version of
the BVID: a description of the user interface and newtools, the products available and some general statistics. A brief study of the ICRF3 sources included in the
BVID data is available in Section 3.

Arnaud Collioud · Patrick Charlot
Laboratoire d’Astrophysique de Bordeaux, Univ. Bordeaux,
CNRS, B18N, allée Geoffroy Saint-Hilaire, FR-33615 Pessac,
France(Correspondence: arnaud.collioud@u-bordeaux.fr)

1 Available at the address https://rorf.usno.navy.mil/RRFID/.

219

220

2 The new version of BVID
The BVID was initially developed in 2008 and officially presented during the 19th EVGA Working Meeting held in Bordeaux in 2009 (Collioud and Charlot,2009). In 2018, we decided to modernize the BVID
and we started the development of the second version of the database, which is detailed in this section.
The BVID may be found at the following address:
http://bvid.astrophy.u-bordeaux.fr.

2.1 Interface
The new version of the BVID has an enhanced clean
and modern interface (Figure 1), which is based on thecurrently available web technologies. The user interface is now more dynamic, and its design is adaptive
to different devices, from mobile phones to computerswith large screens. In addition to the public website,
one can create a user account on the BVID in orderto access additional functionalities and data, manage
downloading information and check favourite sources
or sessions.

Collioud and Charlot

dividual records (i.e. the observation of one source
during one session) that comply with all criteria,
and which can be organized by data, source nameor session name. This is a new functionality of the
BVID version 2.

The new design of the interface is focused on improving the user experience: the search forms are simpler, the query results are as interactive as possible, all
the plots are responsive, data tables can be filtered andexported easily, etc. In particular, we developed a tool
called the “Skymap” which allows one to display thesky distribution of the BVID sources at a given frequency band (Figure 3). Each point is colour-coded
based on the selected parameter (for example the flux
density) and the size of each point represents the number of sessions available for the source. Two distributions are also available below the skymap: one for thenumber of sessions, and the other for the selected parameter. These distributions can be used to filter thesources. Finally, a list of the displayed sources is available at the bottom of the page.

2.3 Products
2.2 Tools
The BVID database can be queried in several ways:• source name: the name to search may be the IERS
name (e.g. 0202+149), the ICRF name (ICRF
J020450.4+151411), any other popular name
(4C15.05, NRAO91, etc.). It is also possible tospecify partial names (0202 or 4C1). This form
allows one to narrow down the search to a single
source and then to display the corresponding page
(Figure 2).
• session name or date, using the dedicated forms or
the timeline of all available sessions.
• source coordinates, by specifying the Right Ascension/Declination and a search radius. Various coordinates formats are allowed (see the help next to
the form).
• multi-criteria: one can specify one or several criteria on the source, the session or the data (flux density, structure index, etc.). The result is a list of in-

The BVID provides VLBI images (in graphical formand FITS format), the underlying source models(CLEAN components files) and the flux density
values. From the source model, we calculate structure
correction delays for all possible baseline lengths andorientations on Earth. These delays are then plottedin the structure correction maps, from which wederive the structure index. This index characterizes themagnitude of the structure corrections for the source(Fey and Charlot, 1997, 2000).
In the same way, we build visibility maps which display the values of the visibility amplitude (normalized
to 1 using the total integrated flux density in the image)for all possible baseline lengths and orientations on
Earth. Visibility maps are used to estimate the sourcecompactness (Charlot, 2008). In addition, ancillary
plots like the uv-plots or plots of the amplitude vs.
uv-radius are available.
To access some products (e.g. the FITS files), it ismandatory to be logged in through a user account.

The Second Version of the BVID

221

Fig. 1: The homepage of the BVID interface presents the latest news, some statistics related to the BVID content and the sky
distribution of all the sources included in the BVID, colour-coded according to their ICRF3 category.

Fig. 2: View of the individual page for the source 0202+149. On top, the timeline displays all the sessions available for that source(here at four different frequencies). On the left-hand side, one can find general information about the source, the tools to visualize
the corresponding data (images, time series, tables) and some general functionalities like the “Add to favourite” tool or the “Source
Download Manager” tool which allows one to easily export and download the data and images available.

222

Collioud and Charlot

3 BVID and ICRF3
Among the 1344 sources comprised in the database,1299 (97 %) are part of ICRF3. In other words, 29 %of the 4536 ICRF3 sources have an image available in
the BVID. More precisely, the BVID comprises 246of the 303 defining sources (81 %) and 1053 of the4233 non-defining sources (25 %). Finally, 45 sources
which originated from other VLBI projects are not partof ICRF3. Using the large amount of data in the BVID,
we can derive and examine the distributions of the median flux density and structure index (SI) at S- and Xband for the defining and non-defining ICRF3 sources.

Fig. 3: View of the “Skymap” tool which allows one to display

and filter sources based on the value of a given parameter (herethe flux density at X-band). In this case, we selected the sources
with a median flux density value larger or equal to 0.5 Jy andwith a number of sessions larger than 15. This leads to a selectionof 92 sources, which can be individually inspected on the sky
distribution or in the source list.

From the median flux distribution (Figure 4), we
conclude that the defining sources are, on average,
twice as strong as the non-defining sources at bothbands, and that the flux density distributions are very
similar for each ICRF3 category. By looking at the median SI distribution (Figure 5), we notice that the median SI for the defining sources is clearly lower thanthat for the non-defining sources. For example, at Xband, the median SI is 2.65 for the defining sourcesand 3.21 for the non-defining sources. This is consistent with the fact that the ICRF3 defining sources werechosen to be as compact as possible.

4 Conclusions
2.4 Statistics

The BVID currently comprises 6117 VLBI maps
produced in Bordeaux, along with 6775 links toimages from the RRFID, for 1344 different sources.
A total of 77 sessions are online (59 RDV sessions,among which 34 were analysed in Bordeaux) at four
frequency bands: S- (2.3 GHz), X- (8.6 GHz), K(24 GHz) and Q-band (43 GHz). On average, there are
4 to 5 sessions available for each source at X/S band,with a minimum number of 1 and a maximum numberof 49. The first session took place in 1994 and the last
one available at present in 2016. The BVID thus covers
a substantial time span of 22 years. Additionally, there
are also 12892 structure correction maps available,
along with the same number of structure indices,
visibility maps and compactness values.

The Bordeaux VLBI Image Database (BVID) delivers
images and information about the structure of the reference frame sources (i.e. structure index) through a refurbished clean and modern interface. It also provides
dynamic tools to query and display the data. The BVID
data may be used for astrometric applications, but isalso useful for astrophysics, e.g. to study jet evolution.
Finally, the BVID is available to host and disseminate
images produced by other groups in the VLBI community with full credits to the author(s). If you are interested, please contact us.
Acknowledgements The authors are indebted to the Observatoire Aquitain des Sciences de l’Univers (OASU) for supporting the development of the second version of BVID. Arnaud
Collioud is also grateful to the Programme National GRAM of
CNRS/INSU with INP and IN2P3 co-funded by CNES for travel
support to attend this conference.

The Second Version of the BVID

223

Fig. 4: Distribution of the median flux density for the ICRF3 defining (left-hand side) and non-defining (right-hand side) sources

included in the BVID. The upper and lower panels are for S- and X-band, respectively. The dashed line in each histogram represents
the median value of the distribution.

Fig. 5: Same as Figure 4 for the median structure index.

References
Charlot P (2008) Astrophysical Stability of Radio Sources
and Implication for the Realization of the Next ICRF. In:
A. Finkelstein, D. Behrend (eds.): IVS 2008 General Meeting Proceedings, 345–354

Collioud A, Charlot P (2009) The Bordeaux VLBI Image
Database. 19th EVGA Working Meeting, 19C
Fey A, Charlot P (1997) VLBA Observations of Radio Reference Frame Sources. II. Astrometric Suitability Based on
Observed Structure. ApJS, 111, 95, doi:10.1086/313017
Fey A, Charlot P (2000) VLBA Observations of Radio Reference
Frame Sources. III. Astrometric Suitability of an Additional
225 Sources. ApJS, 128, 17, doi:10.1086/313382

The Source Structure Effect in Broadband Observations
S. Bolotin, K. Baver, O. Bolotina, J. Gipson, D. Gordon, K. Le Bail, D. MacMillan

Abstract Analysis of the VGOS CONT17 observations showed that the broadband delays are sensitive tobrightness distributions of radio sources. In this presentation we discuss the impact of source structureson the broadband observations and the application ofsource structure models (two points model, multiple
points model, etc.) in data analysis.

Keywords VGOS · Broadband · Source structure0˚The new VLBI Global Observing System (VGOS)
made a great improvement in recent years and reacheda level of maturity. The first publicly available VGOS
observations were made at the end of 2017.
Starting from 1994, VLBI stations participated in
specially designed continuous observation sessions.
Such campaigns of VLBI observations, usually designated as CONT, are conducted roughly every three
years.
The last CONT VLBI campaign, CONT17, wascarried out with three independent networks of VLBI
stations: the legacy, the VLBA and the VGOS networks. While the first two networks observed in theSergei Bolotin · Karen D. Baver · John M. Gipson · David Gordon · K. le Bail · Daniel S. MacMillan
NVI, Inc., NASA GSFC Code 61A, 8800 Greenbelt Road,
Greenbelt, Maryland 20771, USA
Olga Bolotina
5818 Pecking Stone St, New Market, Maryland 21774, USA(Correspondence: sergei.bolotin@nasa.gov)

120˚

180˚

−120˚

−60˚
90˚

60˚

60˚
WETTZ13S
WESTFORD
ISHIOKA

30˚

RAEGYEBGGAO12

KOKEE12M

30˚

0˚

0˚

−30˚

−30˚

−60˚

−60˚

−90˚

−90˚
0˚

1 Introduction

60˚

90˚

60˚

120˚

180˚

−120˚

−60˚

Fig. 1: VGOS stations participated in the CONT17 VLBI cam-paign.

two standard S/X bands, the VGOS network usedbroad band (2 to 14 GHz) to acquire signals from radiosources. Also, to optimize the resources, the VGOS
network observed only five continuous days recording
only half of the possible channels to give a data rate of
8 Gbps instead of the possible 16 Gbps.
As shown in Fig. 1, there were six VGOS stations
that participated in CONT17 campaign: GGAO12M(Goddard, Maryland), ISHIOKA (Ishioka, Japan), KOKEE12M (Kokee Park, Hawaii), RAEGYEB (Yebes,
Spain), WESTFORD (Westford, Massachusetts) and
WETTZ13S (Wettzell, Germany). They started to observe on December 3 and finished on December 8,
2017.
The VGOS observations were correlated at the
MIT Haystack Correlator. Preliminary data analysis
was performed at Goddard Space Flight Center, NASAand the observations now are available for publicaccess at the IVS data centers. Unfortunately, one of
the VGOS stations, RAEGYEB, had a problem with224

Source Structure Effect in Broadband Observations

2 Data analysis

60
GGAO12M:ISHIOKA

hardware during all but first sessions, so it was notincluded in the further analysis.

225

20
0
-20

The number of total (correlated), good (with thequality code greater than 4) and used (in data analysis)
observations as well as weighted post-fit residuals areshown in the Tab. 1. In general, the WRMS of VGOS
sessions are much better than for the legacy S/X sessions with the same parameterization, that are typically
about 8ps.

Table 1: Numbers of total, good and used observations and post-

fit residuals of the VGOS CONT17 sessions.
SessionNtot Ngood Nused
WRMS, ps
17DEC03VG
5999 3800 3533
1.8
17DEC04VG
5037 3775 3519
2.0
17DEC05VG
5833 3987 3765
2.1
17DEC06VG
5166 3461 3224
1.9
17DEC07VG
6043 4168 3937
2.1

During data analysis abnormal distributions of
post-fit residuals for the radio source 0552+398 were
noticed. In Fig. 2, an example of such a distribution
in the session 17DEC04VG is shown for baselines ofthree stations, GGAO, ISHIOKA and KOKEE12M.
The weighted post-fit residuals of the observationsof this radio source are 12ps which is several times
greater than the overall residuals of the session.
The residuals of the source 0552+398 have asimilar pattern for all five broadband sessions. The”standard” data editing procedure would consider
these residuals as outliers and they would be removed
from the data analysis. However, the behavior of theresiduals suggests that there is a systematic effectwhich was not taken into account during data analysis.

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00:00

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08:00

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other sources
0552+398

40
20
0
-20
-40
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00:00

ISHIOKA:KOKEE12M

Baseline vectors, source positions and angles of nutation were estimated as local parameters (i.e., one estimate for each session). Station clock offsets, wet zenith
delays, and atmospheric gradients were estimated as
stochastic parameters using a random walk model.

GGAO12M:KOKEE12M-40

The observations were processed by νSolve software(Bolotin et al., 2016) using the embedded ECMAScript
to treat data uniformly.

other sources
0552+398

40

12/05
04:00

12/05
08:00

12/05
12:00
Time

12/05
16:00

12/05
20:00

other sources
0552+398

40
20
0
-20
-40
12/05
00:00

12/05
04:00

12/05
08:00

12/05
12:00
Time

12/05
16:00

12/05
20:00

Fig. 2: Group delay residuals (ps) for the baselines of GGAO,ISHIOKA and KOKEE12M. Residuals of the radio source
0552+398 are plotted with filled circles, open circles represent
all other radio sources.

3 Modeling the source structure
The first assumption of the nature of the systematic effect was influence of source structure on the observed
group delays. Previous work on the source structure effect in geodetic VLBI observations, Thomas (1980)
and Charlot (1990), discussed point like models ofsource structure and how the models affect group delays and delay rates.
In general, the group delay contribution due to abrightness distribution I(P, ω, t) of a radio source as afunction of coordinates P, circular frequency ω = 2π fand time t can be expressed as
τs =
where

∂Z s
c
Z s ∂Z∂ω − Zc ∂ω

Z s 2 + Zc 2

226

Bolotin et al.

"Zc =I(P, ω, t) cos(ω

b·P
)dΩ
c

I(P, ω, t) sin(ω

b·P
)dΩ
c

"
Zs =

and b is a baseline vector.
First, we investigated a two-point source structure
model. This model consists of two close points, where
the brightness distribution on the sky is (assuming there
is no frequency and time dependence):
I(P) = g1 δ(P − P1 ) + g2 δ(P − P2 )If we choose the origin of structure coordinates at thebrightest point, P1 = 0, and introduce a ratio of amplitudes of the components K = g2 /g1 , then the correction
to the group delay will beτs = −R K(K + cos (2πR))
f 1 + K 2 + 2K cos (2πR)

where the scalar product
R=

b
· P2
λ

and λ is the wave length.
The expression for τ s is simple and can be used inleast squares estimation. The model has two parameters, the scalar K, a ratio of amplitudes of the components and a vector P2 , a distance of the second component from the brightest one. However, the model ishighly non-linear and before using the least squares estimation we need to find appropriate a priori values for
K and P2 . To do this we ran a set of estimations of theratio K for a fixed position P2 and searched for minimal
post-fit residuals for the source 0552+398 as a functionof P2 . The estimations were done in the same way as
described in the Sect. 2, except that K was added to theestimated parameters.
Fig. 3 displays changes of the weighted post-fit
residuals of the source 0552+398 for each estimation.
The lighter areas in the figure correspond to smaller
residuals. There are several areas that could possibly be
used as a priori parameters. Only one of them yields
parameter estimates that are physically meaningful,i.e., the value of ratio of components is 0 < K < 1 andthe process of iterative estimation (when estimates areused as a priori values for the next iteration) converges.
After the initial a priori values of the parameters were found, the data analysis of all five VGOS
CONT17 sessions were performed and the parameters

Fig. 3: Distribution of post-fit residuals of the source 0552+398.

The darker color corresponds the bigger value of the residuals. The x-coordinate (in direction of the right ascension) andy-coordinate (in direction of the declination) correspond to the
fixed position of the second component.
Table 2: Results of estimation the double-point source struc-ture model parameters for the source 0552+398 from the VGOS
CONT17 sessions.
Model parameters
SessionKx, µasy, µasvalue σvalue σvalue σ17DEC03VG
0.385 0.006
900 5−128 8
17DEC04VG
0.352 0.012
930 10−223 20
17DEC05VG
0.390 0.007
900 5−105 10
17DEC06VG
0.384 0.007
905 5−98 1017DEC07VG
0.378 0.007
911 5−155 9of the model were estimated along with the other parameters. Tab. 2 shows values and uncertainties of theestimated ratio of the amplitudes and relative positionof the second component for each session.
Tab. 3 is a statistical summary of the solutions:
number of observations (potentially usable and used ina solution) and WRMS for the source 0552+398. The
WRMS are shown for two cases, when the model was
not applied (”Model:off”) and when the model parameters were estimated (”Model:on”).
As one can see, the results of estimation of the
double-point source structure model for the source
0552+398 are nearly the same for all five VGOS sessions. Applying the model reduces the residuals of thissource to the level of the overall post-fit residuals of aSource Structure Effect in Broadband Observations
Table 3: Statistical information on estimation of the parame-ters of the double-point source structure model from the VGOS
CONT17 sessions: the numbers of potentially usable and usedin data analysis observations of the source 0552+398 and theweighted post-fit residuals of the source without and with themodel.
SessionNumber of obs. 0552+398 WRMS, ps
Usable Used
Model:off Model:on
17DEC03VG
134 132
13.6
2.8
17DEC04VG
118 118
13.5
2.3
17DEC05VG
138 137
13.8
2.6
17DEC06VG
90 90
15.2
3.2
17DEC07VG
149 149
13.3
2.8

GGAO12M:ISHIOKA

60

20
0
-20

GGAO12M:KOKEE12M

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00:00

12/05
04:00

12/05
08:00

12/05
12:00
Time

12/05
16:00

12/05
20:00

other sources
0552+398

40

The point-like model of source structure can be extended to an arbitrary number of points, N. In this casethe brightness distribution can be written as
I(P) = g0 δ(P − P0 ) +NX

gi δ(P − Pi )i=1

We assume that the coordinate system of source structure is centered at the position of the brightest component, P0 . Also, we express the brightness of each component by the ratio to the brightness of the central component, ki = gg0i , where gi < g0 , and use a scalar productRi = bλ Pi . Then, the source structure effect in group delay will be

200τs = −

-20
-40

1 A+B
f Z2

where
12/05
00:00

ISHIOKA:KOKEE12M

Further investigation of VGOS CONT17 observations shows that many sources reveal source structure
effects, although the changes of post-fit residuals forthem are much smaller than for the source 0552+398.
All radio sources with few exceptions that have relatively big declination and were frequently observed
show improvement of the residuals after applying thesource structure model.

other sources
0552+398

40

-40

227

12/05
04:00

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08:00

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Time

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20:00

A=

other sources
0552+398

40

B=

-20

ki Ri (ki + cos (2πRi ))

i=1

20
0

N
X

N−1
N
X X

ki k j (Ri + R j ) cos (2π(Ri − R j ))i=1 j=i+1

-40
12/05
00:00

12/05
04:00

12/05
08:00

12/05
12:00
Time

12/05
16:00

12/05
20:00

Fig. 4: Group delay residuals (ps) for the baselines of GGAO,ISHIOKA and KOKEE12M. Residuals of the radio source
0552+398 are plotted with filled circles, open circles represent
all other radio sources. The double-point source structure model
has been applied.

session. In Fig. 4, the post-fit residuals of the baselinesof stations GGAO, ISHIOKA and KOKEE12M areplotted for the case when the source structure model
has been applied. In contrast to Fig. 2, the systematiceffect in the source residuals is gone.

Z 2 =1 +N
X

NX
ki 2 + 2[ ki cos (2πRi )+

i=1
N−1
N
X X

i=1

ki k j cos (2π(Ri − R j ))]i=1 j=i+1

The procedure of searching the initial values for themulti point source structure model is similar to the twopoint model. First, we search for the second component; if it is found, we estimate model parameters fromdata analysis. After that we fix the obtained parameters
for the second component and search for a third one. If
searching for the a priori reveals physically meaningfulvalues, we can use them in data analysis and estimate

228

Bolotin et al.

Table 4: Results of estimation of a three-point source structure

model for the source 2229+695 in session 17DEC03VG.
Model parametersIdx
Kx, µasy, µasvalue σvalue σvalue σ10.357 0.02
−750 20−120 2020.157 0.03
550 80−160 60the model parameters of the second and third component.
As an example, Tab. 4 shows the result of estimation of the multiple point source structure model inthe case of N = 3 for radio source 2229+695. As one
can see, the standard deviations are significantly bigger
than for the two-point model. By increasing the number of VGOS stations, we expect that components ofmultiple point models will be better resolved.
Fig. 5 illustrates variations of the post-fit residuals
found in searching for the second and third componentsof the multiple point model.

4 Conclusions
Data analysis of the VGOS CONT17 sessions shows asignificant increase of the accuracy of VLBI observations compared with legacy S/X. One consequence of
this is the detection of source structure in the group delays. This effect degrades determination of source positions and EOP; however, it can be taken into accountwith the simple point-like source structure models.

References
Fig. 5: Distribution of post-fit residuals of the source 2229+695.

Bolotin S, Baver K, Gipson J, et al. (2016) Transition to thevgosDb format. In: D. Behrend, K. D. Baver, K. L. Armstrong (eds.): IVS 2016 General Meeting Proceedings,
NASA/CP-2016-219016, 222–224
Charlot P (1990) Radio-source structure in astrometric andgeodetic very long baseline interferometry. AJ, 99, 1309–
1326, doi:10.1086/115419
Niell A., Barrett J, Burns A, et al. (2018) Demonstration of a
Broadband Very Long Baseline Interferometer System: A
New Instrument for High-Precision Space Geodesy. Radio
Sci, 63, 1263-1291, doi:10.1029/2018rs006617
Thomas J B (1980) An Analysis of Source Structure Effects inRadio Interferometry Measurements. NASA-JPL Publ. 80–
84

On the top: searching for the a priori values of the second component of the model. On the bottom: searching the third component.

Source Structure Effects in Next-generation VLBI
Observations
S. Salarpour, S. Shabala, L. McCallum, J. McCallum, L. Chin Chuan

Abstract Next-generation VLBI (VGOS) may struggle with the source structure issue to determine accurate celestial and terrestrial reference frames. Observations over a wide bandwidth of 2 − 14 GHz will be influenced by source structure which is highly frequency
dependent. Moreover, the structure of a quasar often
evolves on timescales of months. To calculate visibility phase changes over the broadband frequency range,
the source structure module of the Vienna VLBI Software (VieVS) is extended. So far, we have focused on asingle source (J0136+4751) to obtain these effects as afunction of frequency and time for varying geometries.
By using this approach and simulated VGOS networks,
we can estimate the number of observations within asession that may be affected by source structure on thedependence of the source’s evolution over time, as wellas baseline length and observing geometry.

Keywords Quasar · VLBI · Source Structure · VGOS

1 Introduction
Very Long Baseline Interferometry (VLBI) is a space
geodetic technique used to define terrestrial and celestial reference frames by measuring the stations andquasars positions respectively. VLBI geodesy requires
to observe bright and compact (ideally point-like)
Simin Salarpour · Stanislav Shabala · Lucia McCallum · Jamie
McCallum · Lim Chin Chuan
University of Tasmania, School of Natural Sciences, Private Bag
37, Hobart, AU-7001 Australia(Correspondence: simin.salarpour@utas.edu.au)sources, which are stable both in time and frequency.
These requirements are challenging. Quasars haveoften extended structure on milliarcsecond scales e.g.
Charlot (1990); Fey et al. (1996). The structure dependency on time and frequency put restrictions on source
positions and consequently on VLBI observations(Plank et al., 2016; Shabala et al., 2014; Tornatore &Charlot, 2007). Although the source structure effects
are usually considered as systematic errors in legacy
VLBI at the millimetre level (Shabala et al., 2015),
these effects could be a hurdle for the next generation
VLBI system.
The VLBI Global Observing System (VGOS) isbased on finding broadband delay. In this system,
quasars are observed with 12-m radio telescopes infour frequency bands between 2–14 GHz range (Niell
et al. , 2007). The broadband delay calculation will
be difficult in the presence of quasar structure thatprevents phase connectivity through four VGOS bands(Petrachenko et al., 2016). So far, some work has been
done to address and determine the source structure
effects in broadband frequency e.g. Niell (2006a,b).
In this research, we investigate the time evolutionof a source by looking at the time series of total flux
density and structure index. By developing Niell’s idea
(Niell, 2006a,b), we construct a frequency-dependentsource model using real images at different frequencies. The current source structure module of VieVS(Böhm et al., 2018; Shabala et al., 2015) is used to simulate real observations in the presence of source structure. We also estimate the source structure effects infuture VGOS network observations. This research will
help to improve the scheduling of observations, basedon the combination of broadband source structure andgeometry.
229

230

Salarpour et al.

5

5

4

4

3

3

2

2

1

1

0
1996

2000

2004

2008

2012

2016

Structure Index

Flux density (Jy)

Total flux density
Structure Index

0
2020

Time (years)
Fig. 1: Total flux density and structure index time series at

8.6 GHz, source J0136+4751.

density: changes in beaming (Lister et al., 2009), andintrinsic changes in jet power (Cao, 2003). The unresolved part of the jet (core component) is the innermost and optically thick region. When the source ejects
new components and the jet becomes optically thin, it
is known as a flaring event. This event can be recognized from the peak in time series of total flux density (Blandford et al., 1979). The core component isgetting brighter and at its most compact during flarein the total flux density. Changes in the source structure can be seen from variations of the measured structure index which is anti-correlated with the fluctuations of total flux density (Shabala et al., 2017). In Figure 1, between 2002 and 2004 we expect a flare andas a result, a compact source compared to 2006 when
probably the source is more extended. In the next section, these structure changes will show their impact on
multi-frequency simulations of VGOS observations.

2 Method
2.2 Source model
2.1 Image processing
After a search among well-observed ICRF2 sources
and the Astrogeo (http://astrogeo.org/ ) image database,
J0136+4751(0133+476) was chosen. J0136+4751 is avariable source which is frequently observed and often
has structure. For this source, there were 59, 71, and 39
images in S (2.3 GHz), X (8.6 GHz), and U (15.4 GHz)bands respectively available. We took advantage of automated scripts to find a functional source model basedon Gaussian fitting at each epoch and frequency. The
automated scripts provide flux density, size, and position parameters for each component of a source, which
are required to construct the source model and evolution over time at different frequencies. Figure 1 showssource structure and total flux density evolution overtime which have been obtained from automated scripts.
We note that the total flux densities obtained from thefitted code are in good agreement with the total flux
densities extracted from the image header. In this case,an average of 89 % of integrated flux density is recovered.

2.1.1 Time evolution

Figure 1 shows the time variability of the source. There
are two main reasons to see fluctuations in total flux

The Gaussian fitting is applied to the images to findsource components and their positions using automatedscripts. Our frequency dependent source model is suggested by Niell (2006a,b). This model is defined by flux
density, size, and position parameter of each sourcecomponent as well as spectral indices below and above
the turnover frequency. The spectral indices have beenobtained based on the flux densities at different frequencies and they are time-dependent parameters. The
turnover frequency of the core component occurs at
higher frequency whereas for other extended components, it can be observed at lower frequencies. Leftplot in Figure 2 is an example of our source modelfor one time epoch. We have used X-band images as
proxy for the whole VGOS frequency range (Salarpour
et al., 2018). The measured visibility phase based on
this model is highly dependent on time and frequency.
Along with this time and frequency dependency, geometric variations also have a significant impact (Figure 2, right plot).
The visibility phase is a function of baseline lengthand projected jet direction. The structure effect of an
extended source on visibility phase is different for various baseline angles (Figure 2 (right), solid line). Thereis no structure contribution to the visibility phase when
the baseline is perpendicular to the jet direction (Charlot, 1990; Shabala et al., 2015). For other jet angles,

Source Structure in VGOS

Frequency (GHz)231

Frequency (GHz)

Fig. 2: Left: source model with four jet components. Right: vis-

Fig. 3: Visibility phase obtained from the source model over aibility phase changes with respect to different geometry over abroad bandwidth. Solid lines (yellow, red, and blue) are the samebaseline length in different angles; dot lines (green and black) are
different baseline lengths with the same angle as blue solid line.

broad bandwidth (2 to 14 GHz). Right: J0136+4751 with SI =2.5 in 2011; Left: the source with SI = 0.6 in 2000. Each line
represents one observation of the schedule.

3 Results
we expect to see quasar structure effect. Figure 2 (rightplot, dotted line) also shows that rapid phase changes
related to source structure effect are detectable at lower
frequencies for longer baselines.

There are two questions here: 1. How does the source
structure affect a 24-hour observation session for variable structure over time? 2. What is the baseline geometry role in source structure effect detection? In thefollowing, we will examine these two issues.

2.3 VieVS simulation
3.1 Effects of changing source structure
For more realistic results and predicting future experiments, simulation tools are used. The schedule issimulated as a 24-hour session using the VieSched++(Vienna VLBI Scheduling Centre) (Schartner andBöhm, 2019), an improved standalone scheduling
tool derived as part of the VieVS. Standard catalog
files from the SKED website are used. The source
0133-476 (J0136+4751) is selected from the VieSched++ graphical user interface to be observedwith 10 stations which are, or expected to be involvedin the VGOS experiments. The selected stations are
GGAO12M, HART15M, ISHIOKA, KATH12M,
KOKEE, NYALES20, ONSA13SW, RAEGYEB,WETTZ13N, and YARRA12M, where each stationis scheduled to observe the source once every 10
minutes. Since only one source is selected in theschedule, fill-in mode and subnetting do not influence
the schedule output. For this test network, we found
144 scans and 2460 observations to this single source.
The visibility phase for each observation and baseline
are calculated by using the source structure module of
VieVS (Shabala et al., 2015).

The visibility phase derived from the model indicatessudden changes over broad bandwidth at those epochs
in which the source tends to show more structure. By
contrast, the phase changes are well-behaved when
the source is more compact. As an example, Figure 3
demonstrates phase changes from 2 GHz to 14 GHz
for two different epochs that J0136+4751 has different
structure indices: an SI of 0.6 corresponds to a compact source, while SI = 2.5 is a source with extended
structure. In this figure, each colour line stands for one
observation in a 24-hour session. While in compact
source times no rapid changes were detected (3, leftplot), visibility phase was varied quick by the extended
structure (3, right plot). We assume a flat spectrum
source, i.e. the source structure appears the same at
all frequencies. Charlot (1990) showed that the source
structure will have a contribution to the group delay
when the observed phase varies with frequency. Such
rapid phase changes (phase wraps) are a challenge for
VGOS that aims to observe sources in four frequency
bands spread over 2 to 14 GHz. This problem is exacer-

232

Salarpour et al.

bated when attempting to connect phases across VGOS
bands. Phase wraps can even prevent phase connectivity.

3.2 Baseline effects
According to the results for SI = 2.5 (2011), in 24-hoursession observations with the selected VGOS network,baselines with the length shorter than 8000 km are notaffected by adopted source structure. Figure 4 shows
the affected observations percentage (Red diamonds)
and phase wraps distribution in each baseline (Blueboxes). In each blue box, which represents the phasewraps distribution, the central mark is the median value
while the bottom and top edges are 25th and 75th percentiles. As an example, the phase wrap distribution
for baseline 9500 Km (KOKEE-YARRA) is from 12 to
13 GHz and the affected observations fraction is 20 %.
In this Figure, one sees, the fraction of affected observations is increasing with baseline length. This is due
to a better resolution of longer baselines (Middelberg& Bach, 2008). At the same time, it is shown that the
point of phase wrap occurrence moves towards lower
frequencies. The distribution of these frequencies, as
shown in Figure 4, is broader for longer baselines. This
would make predicting the VGOS frequency band mostaffected by source structure very challenging- for example, it will highly depend on knowing the source
structure to high precision. The percentage of troublesome observations sometimes exceeds 50 percent insome baselines which is not good at all for VGOS. It
should be kept in mind that due to the Earth rotation,
the projected jet angle is changed for a specific baseline (Plank et al., 2015). This causes all observationsof a source by that baseline not to be equally affectedby the source structure.

4 Conclusions and outlook
We used source images to study the flux density
variability of ICRF2 quasars. Most sources havemilliarcsecond level of structure, and this structureoften evolves with time. Besides the time variability,
the quasar structure is highly dependent on frequency.
This is a challenge for VGOS observations which
aim to observe in wide range frequency. We made afrequency dependent source model of J0136+4751
to study source structure effects on broad bandwidthobservations. We show that source structure can cause
rapid changes in visibility phase, creating a problem
for phase connectivity through four VGOS bands andmaking it challenging to find a group delay. Using

60
50

Frequency (GHz)

13
40
12
30
11
20
10

Affected observations (%)

14

10
9
8100

9500

10100

10800

11500

0
12100

Baseline Length (Km)Fig. 4: Phase wraps distribution and percentage per baseline for a 24-hour session observing J0136+4751 in 2011 (SI = 2.5).

Source Structure in VGOS

the VieVS structure module helps us to find quasar
structure effects on visibility phase for a selected
VGOS network. The observed effects of an extended
source in various baselines at broad bandwidth are
different due to the baselines’ geometry. In a fictitious
VGOS schedule of a global network observing a single
source over 24 hours, a significant fraction (up to50 %) of longer baselines can be affected due to bettersource structure resolution.
Applying our approach to more well-observed
sources as well as improving the fitting routines will
provide more precise frequency-dependent models toinvestigate source structure effects. While up to now
our broadband structure investigations mostly rely
on images at X band, we would like to add-in also
information from other frequencies if available. We
hope to connect our theoretical findings with future
UTAS VGOS observations. We also hope that thecontribution of this work and more studies concerning
careful source selection, network geometry and observing time may help to avoid source structure effects
in the next generation geodetic VLBI observations.

References
Blandford R, Königl A (1979) Relativistic jets as compact radiosources. ApJ, 232
Böhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and satellite software (VieVS) for geodesy and astrometry. PASP,
130(986), 044503
Cao X (2003) Jet formation in BL Lacertae objects with different
accretion modes. ApJ, 599(1), 147
Charlot P (1990) Radio-source structure in astrometric andgeodetic very long baseline interferometry. AJ, 99, 1309
Fey A L, Clegg A W, Fomalont E B (1996) VLBA Observationsof Radio Reference Frame Sources. I. ApJS, 105, 299

233

Kovalev Y Y, Ros E, Savolainen T et al. (2009) MOJAVE: Monitoring of jets in active galactic nuclei with VLBA experiments. V. multiepoch VLBA images. AJ, 137(3), 3718
Middelberg E, Bach U (2008) High resolution radio astronomy
using very long baseline interferometry. Rep. Prog. Phys.,71(6), 066901
Niell A (2006a) Source Structure Simulation. IVS Memorandum 2006-017v01, ivscc.gsfc.nasa.gov/publications/memos/
ivs-2006-017v01.pdf
Niell A (2006b) Source Structure Examples. IVS Memorandum 2006-018v01, ivscc.gsfc.nasa.gov/publications/memos/
ivs-2006-018v01.pdf
Niell A, Whitney A, Petrachenko W, et al. (2007) VLBI2010: A
Vision for future geodetic VLBI. Dynamic Planet, 757–759
Plank L, Lovell J, Shabala S, et al. (2015) Challenges for geodetic VLBI in the southern hemisphere. ASR, 56, 304
Plank L, Shabala S, McCallum J, et al. (2016) On the estimation of a celestial reference frame in the presence of source
structure. MNRAS, 455, 343
Petrachenko B, Charlot P, Collioud A, et al. (2016) VGOS
Source Selection Criteria. In: D. Behrend, K. D. Baver,K. L. Armstrong (eds.): IVS 2016 General Meeting Proceedings, NASA/CP-2016-219016, 82–86
Salarpour S, McCallum L, Shabala S, et al. (2018) Investigating
quasar structure in VGOS with simulations. In: K. L. Armstrong, K. D. Baver, D. Behrend (eds.): IVS 2018 General
Meeting Proceedings, NASA/CP-2019-219039, 88–92
Schartner M, Böhm J (2019) VieSched++: A New VLBI
Scheduling Software for Geodesy and Astrometry. PASP,
131(1002), 084501
Shabala S, Rogers J, McCallum J, et al. (2014) The effects offrequency-dependent quasar variability on the celestial reference frame. J Geod, 88(6), 575
Shabala S, McCallum J, Plank L, et al. (2015) Simulating the effects of quasar structure on parameters from geodetic VLBI.
J Geod , 89(9), 873
Shabala S, Plank L, Schaap R, et al. (2017) The effects of simulated and observed quasar structure on the VLBI reference
frame. IAG Symposia, 146, 191–199
Tornatore V, Charlot P (2007) The impact of radio source structure on European geodetic VLBI measurements. J Geod, 81,469

VLBI Analyses at the National Geographic Institute of Spain(IGN)
E. Azcue, V. Puente, S. Garcia-Espada, Y. Gómez Espada, M. Valdés

Abstract Beyond taking part over the last decades
through the participation of the Astronomical Centerof Yebes on VLBI observations and the development of
the RAEGE project for an Atlantic Network of Geodynamical and Space Stations, the National Geographic
Institute of Spain (IGN) is committed to expand its
contribution to geodetic VLBI in terms of data analysis. An analysis team has been working on the data
analysis with different software packages for the last
two years. In this work, the results of the last processing campaigns using different software packages arepresented, as well as several comparisons in order totest the solution.

Keywords Analysis · VieVS Software · VLBI · Where
Software

1 Introduction
Over the last years, the National Geographic Instituteof Spain (IGN) has been strongly involved in technical aspects of geodetic VLBI. In this sense, it should
be highlighted its participation on observation campaigns through the Astronomical Center of Yebes (withthe 14-m radio telescope -Yb- in Yebes from 1995 toEsther Azcue · Yaiza Gómez Espada · Vı́ctor Puente ·Marcelino ValdésInstituto Geográfico Nacional
C/General Ibañez de Ibero, Madrid, Spain
Susana Garcia-Espada
Instituto Geográfico Nacional - RAEGE Santa Maria station,
Azores, Portugal(Correspondence: eazcue@fomento.es)

2003 and the 40-m radio telescope -Yg- from 2008 topresent) or the development of the RAEGE project for
an Atlantic Network of Geodynamical and Space Station, setting up a Spanish-Portuguese network of four
Geodetic Fundamental Stations (two of them, Yebes Yj- and Santa Maria -Sa- VGOS antennas, are alreadyoperational). At present, the National Geographic Institute of Spain (IGN) is committed to expand its contribution to geodetic VLBI. For this reason an analysis team has been established. For the last two years
several test with different software packages has been
performed.

In Azcue et al. (2019) first results of VLBI processing carried out at IGN were shown. Two VLBI software
packages were used for experimentation activities inorder to compare and validate the solution beyond thesoftware used. These tools were VieVS 3.0 (Böhm etal., 2018) and Where v0.8.1 Kirvirk2 017.

Currently, The IGN analysis team continues withseveral VLBI processing activities such as the routinary processing of R1 and R4 sessions using Where(and contrasted with VieVS processing) or diverse research activities using both softwares.

In this work, the estimated Earth Orientation Parameters (EOP) for the period spanning from to 2002
to 2018 obtained using Where v0.16.3 are presented.
These outputs are compared to the those from Analysis
Centers which are consistent in terms of configuration,
specifically concerning terrestrial and celestial frames
and IERS models (Petit and Luzum, 2010).
234

VLBI Analyses at IGN

235

2 Processing strategy

4 Conclusions and future plans

Where v0.16.3 software package has been used to process R1 and R4 VLBI sessions for the period spanning from 2002 to September 2018. The summary of
the configuration used is shown in Table 1. The set of
estimated parameters is the following:

The results presented in this work lead to conclude thatthe accuracy of IGN solution is, in general, within thesame order of magnitude than other VLBI Analysis
Centers.
An odd behaviour has been detected regarding Celestial Pole Offsets. For the period processed, it would
be expected to get a sinusoidal pattern due to Free Core
Nutation but this is not the case.
In the light of these results, IGN team is driven
to contribute as much as possible to IVS analysis activities. In this respect, in January 2019 a bid to become potential analysis center was submitted to the
IVS Combination Center.

• Station and source coodinates.
• EOP (polar motion and rates, UT1, LOD and celestial pole offsets).
• Station clock (1 h interval).
• Zenith troposphere delay (1 h interval) and gradients (6 h interval) per station.

Table 1: Summary of the configuration

FramesICRF2 and ITRF14
IERS Conventions
2010
EOP a priori
C04 series
Precession/nutation model IAU 2006/ IAU 2000A
Troposphere
VMF1 model
Geophysical models
solid tide
tidal ocean loading (TPXO.7.2)
solid and ocean pole tides
atmosphere tides
thermal antenna deformation
Estimation model
Kalman Filter

3 Results
EOP differences for the period analysed with Where
v0.16.3 have been compared to EOP 14 C04 series (Bizouard et al., 2019). The same comparison has been
carried out using EOP estimated by other Analysis
Centers such as BKG, GSF, OPA and USN, as well aswith the IVS combined solution. These solutions wereretrieved from IVS ftp (Nothnagel et al., 2017). Differences shown in Figure 1 are shifted in y axis for eachAnalysis Center for the sake of clarity. Mean value andpercentile 95th of the differences for each solution are
shown in Table 2. Percentile 95th is used instead ofstandard deviation to avoid the influence of some outliers present in the series.

References
Azcue E, Gómez Espada Y, Puente V, etal. (2019) Initial
VLBI Data Analyses at the National Geographic Instituteof Spain. In: K. L. Armstrong, K. D. Baver, D. Behrend(eds.): IVS 2018 General Meeting Proceedings, NASA/CP2019-219039, 233–236
Bizouard C, Lambert S, Gattano C, et al. (2019)
The
IERS EOP 14C04 solution for Earth orientation parameters consistent with ITRF 2014. J Geod 93(5), 621–633,
doi:10.1007/s00190-018-1186-3
Böhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry. PASP,
130, 986, doi:10.1088/1538-3873/aaa22b
Kirvirk A-S, Hjelle G A, Dahnn M, et al. (2018) WHERE —A New Software for Geodetic Analysis. In: R. Haas, G. Elgered (eds.): Proc. 23rd EVGA Working Meeting, 248–252
Nothnagel A, Artz T, Behrend D, et al. (2017) International VLBI Service for Geodesy and Astrometry – Delivering high-quality products and embarking on observations of the next generation. J Geod, 91(7),711–721,
doi:10.1007/s00190-016-0950-5
Petit G, Luzum B (2010) IERS Conventions. IERS TechnicalNote, 36, Frankfurt am Main: Verlag des Bundesamts für
Kartographie und Geodäsie

236
Fig. 1: EOP differences with respect to EOP 14 C04 series.

Azcue et al.

VLBI Analyses at IGN

237

Table 2: Statistical summary of the EOP differences for each solution with respect to EOP 14 C04 series (2002-2018).

EOP Parameter BKG GSF IVS OPA USN
IGN
Samples2710 2889 2226 3048 20781595
xp (mas)Mean 0.18 −0.03 −0.01 0.05 −0.25 −0.20
P95 0.56 0.39 0.20 0.88 −0.02
0.89
yp (mas)Mean 0.24 −3.57 −0.02 −0.01 0.02 −0.09
P95 0.89 0.60 0.41 0.19 0.49
0.24
UT (ms)Mean −0.13 2.54 −0.10 −0.11 −0.15 −0.13
P95 0.03 0.04 0.02 0.07 0.02
0.12
dX (µas)Mean −1.94 23.29 12.62 57.75 −9.66
2.41
P95 176.99 207.66 79.69 186.99 89.62 1599.62
dY (µas)Mean 8.87 −10.15 −1.21 110.65 8.59 −26.62
P95 180.74 174.90 71.92 230.80 111.09 1622.31

Earth Orientation Parameters Estimated From K-band VLBA
Measurements
H. Krásná, D. Gordon, A. de Witt, C. S. Jacobs, B. Soja

Abstract The Earth Orientation Parameters (EOP),
which connect the Terrestrial and Celestial Reference
Frame, are regularly estimated by Very Long Baseline
Interferometry (VLBI). The UT1-UTC and nutation
components of EOP can only be measured using
the VLBI technique. Until recently, published VLBI
estimates of EOP were based solely on observations
from the S/X frequency band.
We present VLBI estimates of EOP from an observing
frequency independent of the traditional SX-band
using Very Long Baseline Array (VLBA) measurements at K-band (24 GHz, 1.2 cm). We have over
two years of regular VLBA experiments conductedwith telescopes located in U.S. territory. We investigate the potential of K-band VLBI to produce moreaccurate EOP because of its reduced source structure
effects relative to S/X-band. We compare our K-band
EOP computed with two analyses software packages(Calc/Solve and VieVS) to the IERS C04 data.

1 Introduction and data
In this paper we present solutions containing 69
K-band VLBI observing sessions with the first one in
May 2002 and the last one in January 2019. From thatamount, 52 sessions were observed with the VLBA
network on the U.S. territory (15 sessions before2015). The remaining 17 experiments are the single
baseline sessions between HartRAO and Hobart26
which makes less that 1 % of the total number ofK-band observations. In these single baseline sessions
the Earth Orientation Parameters (EOP) were fixed in
the analysis to their a priori values and the sessions
are used mainly to strengthen the Celestial Reference
Frames (CRF) estimation.
The data rates increased significantly from 128 to256 Mbps before 2015 to 2048 Mbps after the year
2015. After the Mark6 recorder upgrade a data rateof 4096 Mbps is anticipated. For further information
about the K-band project we refer to de Witt et al.
(2019); Le Bail et al. (2019); Soja et al. (2019).

Keywords K-band · EOP · VLBA · VLBI

Hana Krásná
Technische Universität Wien, Vienna, Austria
Astronomical Institute, Czech Academy of Sciences, Prague,
Czech RepublicDavid Gordon
NVI, NASA Goddard Space Flight Center, USA
Aletha de Witt
SARAO/HartRAO, South Africa
Christopher S. Jacobs · Benedikt Soja
Jet Propulsion Laboratory, California Institute of Technology,
USA(Correspondence: hana.krasna@geo.tuwien.ac.at)

2 Parametrization
We show two independent solutions of the EOP. The
GSFC-k-190207 was computed at the Goddard Space
Flight Center with the software package Calc/Solveand the TUW-k-190223 was processed at the Technische Universität Wien with the VieVS software package (Böhm et al., 2018) using the NGS cards as input.
Some of the differences between the TUW and GSFC
solution are, e.g., that GSFC includes delay rates to theanalysis, and that the Galactic aberration was modeled
and applied in the GSFC solution to give source posi238

EOP From K-band VLBA

239

tions at the 2015.0 epoch.
In both solutions the same global parameters were estimated. The Terrestrial Reference Frame (TRF) was
realized with the VLBA station positions and linear
velocities for epoch 2010 with applying the No Net
Translation (NNT) and No Net Rotation (NNR) condition w.r.t. ITRF2014. The celestial reference frame
was estimated with source positions where the TUWsolution used an unweighted NNR w.r.t. ICRF2 defining sources, whereas the GSFC solution applied an
unweighted NNR constraint on 193 ICRF3 defining
sources.
For the session-wise estimated parameters we used asimilar parametrization in both solutions:• TRF — station position of HartRAO, Hobart26,
Tianma65, Tidbinbilla70• Clock parameters — 60 min estimation intervals• Zenith wet delay — continuous piece-wise linear
offsets in 30 min intervals with 1.5 cm relative constraints• Troposphere gradients -– continuous piece-wiselinear offsets in 360 min intervals with 0.05 cm relative constraints• EOP — 1 offset per session from VLBA• EOP from single baseline sessions were fixed to
IERS 14 C04 combined series (Bizouard et al.,2019).

Table 1: Median formal error of the estimated EOP.

x pole[µas]

GSFC-k-190207(pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)y pole
GSFC-k-190207[µas](pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)
dUT1
GSFC-k-190207[µs](pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)
nutation dX GSFC-k-190207[µas](pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)
nutation dY GSFC-k-190207[µas](pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)

median formal error
71
109 / 5880
168 / 7289
184 / 78108
288 / 976
9/5
7
17 / 64254 / 3850
78 / 4541
58 / 3449
72 / 40

Ionosphere corrections were estimated from 2 hour average JPL GPS ionosphere maps by David Gordon andapplied in both solutions.

3 Results
Plots in the left-hand side column in Fig. 1 show thesession-wise estimated offsets w.r.t. the IERS 14 C04
EOP from the VLBA sessions, and in the right-handside column the respective formal errors are depicted.
The black colour represents the GSFC-k-190207 solution, the light red colour the TUW-k-190223 solution,and the formal errors of the IERS 14 C04 EOP are depicted with blue plus signs. In the Table 1 the median of
the formal errors of the two EOP solutions is summarized. In addition we distinguish between the data sets
before the year 2015 and after 2015. We see a decreaseof the median formal error in all five EOP after 2015of about a factor of two. Table 2 shows statistics for
the EOP estimates w.r.t. IERS 14 C04 time series, suchas the weighted mean, median, wRMS, χ2 and normalized deviation from unity (χ2 −1)/σ(χ2 ). Post-2015
wRMS scatter is noticeably improved for the polar motion. However, nutation do not improve much except
for Vienna dX nutations. Offset in the y-pole component is related to the VLBA telescope distribution. Future investigations will be devoted to understand why
the offset in the y-pole component is so prominent in
the TUW-k-190223 solution.

4 Conclusions and outlook
Reasonable EOP series can be produced from the
K-band VLBA measurements. Comparison of two
independent global adjustments computed with two
software analysis packages (VieVS and Calc/Solve)
is shown. Future plans: We anticipate a factor of 1.4
increase in sensitivity from doubling the data rates to4096 Mbps. Testing of the new rate will start this year.
Operations may begin in 2019/20. Both the Celestial
and Terrestrial Frames should improve with time
thereby improving EOP.

240

Krásná et al.

Table 2: Statistics of the difference between estimated EOP and IERS 14 C04.

x pole

GSFC-k-190207(pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)y pole
GSFC-k-190207(pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)
dUT1
GSFC-k-190207(pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)
nutation dX GSFC-k-190207(pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)
nutation dY GSFC-k-190207(pre-2015 / post-2015)
TUW-k-190223(pre-2015 / post-2015)

weighted mean[µas, µs]
−49 / 272

median[µas, µs]
−30 / 299wRMS[µas, µs]
249 / 143

χ2[–]
3.69 ± 0.38 / 3.29 ± 0.24

(χ2 − 1)/σ(χ2 )[–]7.11 / 9.71

−102 / 185−164 / 218

270 / 165

1.92 ± 0.38 / 3.34 ± 0.24

2.42 / 9.94

−160 / 189−287 / 232

504 / 2037.20 ± 0.38 / 5.42 ± 0.24

16.41 / 18.76−1228 / −72−1119 / −89 344 / 201

1.28 ± 0.38 / 3.56 ± 0.24

0.74 / 10.85

15 / −14

15 / −14

37 / 52

10.48 ± 0.38 / 11.52 ± 0.24

25.08 / 44.63

16 / −18

4 / −18

38 / 52

3.88 ± 0.38 / 10.57 ± 0.24

7.61 / 40.62−120 / −18−106 / −45 137 / 129

4.10 ± 0.38 / 3.66 ± 0.24

8.21 / 11.29−66 / 58

−97 / 20133 / 105

12.98 ± 0.38 / 4.41 ± 0.24

31.69 / 14.48−32 / −67

−62 / −58

105 / 1092.44 ± 0.38 / 2.98 ± 0.24

3.80 / 8.42

−39 / −62

−51 / −53

98 / 1047.25 ± 0.38 / 5.59 ± 0.24

16.53 / 19.46

Acknowledgements We acknowledge our respective sponsors:
HK acknowledges the Austrian Science Fund (FWF, ProjectT697-N29). SARAO/HartRAO is a facility of the National Research Foundation (NRF) of South Africa. Portions of this work
done at Jet Propulsion Laboratory, California Institute of Technology under contract with NASA. We gratefully acknowledge
the grant of observing time on the VLBA under the USNO time
allocation. Copyright © 2019. All rights reserved.

References
Bizouard C, Lambert S, Gattano C, et al. (2019) The IERS EOP
14C04 solution for Earth orientation parameters consistent
with ITRF 2014. J Geod, 93, 621–633, doi:10.1007/s00190-

018-1186-3
Böhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry. PASP,
130/986, 1–6, doi:10.1088/1538-3873/aaa22b
de Witt A, Gordon D, Jacobs C S, et al. (2019)
The
K-band (24 GHz) Celestial Reference Frame.
Posterat the 24th EVGA Working Meeting, http://www.oan.es/
evga2019/EVGA2019 PDF/P306 EVGA2019 deWitt.pdf
Le Bail K, de Witt A, Jacobs C S, et al. (2019) Time stability of
the K-band catalog sources. In: R. Haas, S. Garcia-Espada,J. A. López Fernández (eds.): Proc. 24th EVGA Working
Meeting, 209–213
Soja B, Jacobs C S, Runge T, et al. (2019) Ionospheric calibration for K-band celestial reference frames. Presentation
at the 24th EVGA Working Meeting, http://www.oan.es/
evga2019/EVGA2019 PDF/O316 EVGA2019 Soja.pdf,
doi:10.13140/RG.2.2.34409.95840

EOP From K-band VLBA

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Fig. 1: On the left-hand side EOP offsets w.r.t. the IERS 14 C04 values are shown and on the right-hand side the respective formal

errors. The GSFC-k-190207 solution is plotted in black, the TUW-k-190223 solution in light red, and the formal errors of the
IERS 14 C04 EOP are depicted with blue plus signs.

AUA047: Students at TU Wien Organize Their own VLBI
SessionH. Wolf, M. Schartner, J. Gruber, J. Böhm, L. McCallum, J. McCallum, W. Hankey

Abstract At Technische Universität Wien (TU Wien)
students had the chance to fully organize the official
IVS session AUA047. We will give an overview of
the individual parts of this course, including, scheduling, large-scale Monte Carlo simulations, an correlation exercise and analysis. The workflow of carryingout the AUA047 VLBI session using the Vienna VLBI
and Satellite Software (VieVS) and the new scheduling
tool VieSched++ is described. We provide, as well, thescheduling statistics achieved with VieSched++ andthe results of the analysis.

cluding large-scale Monte-Carlo simulations, scheduling, correlation and analysis. As a result of a cooperation with the University of Tasmania, it was possible
to observe the VLBI session successfully with Australian telescopes. The participating stations were Hobart (26 m), Katherine and Yarragadee, shown in Figure 1.

Keywords IVS, scheduling · Large-scale Monte Carlosimulations · Correlation · Analysis · VieSched++ ·VieVS

1 Introduction

Fig. 1: The network of the AUA047 session consisting of

Hobart (26m), Katherine and Yarragadee.

As part of the lecture “Space Geodetic Techniques” at
TU Wien, students organized an official VLBI sessionof the International VLBI Service for Geodesy and Astrometry (IVS) (Nothnagel et al., 2017). The experiment is part of the AUSTRAL VLBI program (Plank
et al., 2017) with the session code AUA047. Observation start was the 4th of December 2018. More than 30
students participated in this course and worked independently in groups to perform all necessary steps, inHelene Wolf · Matthias Schartner · Jakob Gruber · Johannes
Böhm
TU Wien, Department of Geodesy and Geoinformation,
Gußhausstraße 27-29, AT-1040 Wien, Austria
Lucia McCallum · Jamie McCallum · Warren Hankey
University of Tasmania, Private Bag 37, 7001 Hobart, Australia(Correspondence: helene.wolf@geo.tuwien.ac.at)

2 Scheduling
Schedules were created by each group independently
using the software VieSched++ (Schartner and Böhm,2019). The students could decide if they want to
optimize the schedule for a geodetic, astrometricor intensive-like purpose. For this optimization the
VieSched++ multi-scheduling tool was used. The
students investigated the impact on the schedule ofusing different optimization criteria such as, number ofobservations, sky coverage, scan duration, maximum
allowed idle time and minimum number of stations
per scan. Additionally, the individual weights of the
243

244

Wolf et al.

Fig. 2: VieSched++ statistics tool for comparing created schedules using the multi-scheduling tool. The bars symbolise the relativevalue of parameters such as, number of scans (blue), number of observations (green) and weight factors (red, orange, purple).

Fig. 3: VieSched++ Analyzer displaying the sky coverage of the in the session included stations, with dots representing observed

sources, color-coded by the different cable wraps, counterclockwise (red), neutral (green) and clockwise (blue). The smaller grey
dots represent the sources which are not observed in the selected time span.

stations were investigated with focus on the station
Hobart, as this is the slowest but most sensitive station.
Figure 2 shows the VieSched++ statistics tool
which was used for comparing the statistics of thecreated schedules. This tool allows the ranking of theschedules according to different properties, like forexample, number of scans or number of observations.
The evaluation of a schedule was also done using the
VieSched++ Analyzer, shown in Figure 3. This tool
displays the sky coverage of the involved stations.

Therefore it allows a comparison of the created schedules based on the distribution of observed sources.
In total, several hundred schedules were created
and further simulated and analysed using the Vienna VLBI and Satellite Software (VieVS) (Böhm
et al., 2018). The schedule from one group wasselected based on simulated repeatability values andsuccessfully observed with the Australian telescopes.
Table 1 shows the achieved scheduling statistics ofthe observed schedule. It is worth mentioning that thestudents optimized the schedule, so that the antennas inAUA047: Student VLBI Session

245

Table 1: Scheduling statistics of the observed schedule createdusing VieSched++
AUA047
number of scans
number of observations
number of scheduled sources
average observing time
average slew time
average idle time

513
1358
66
58.65 %
30.11 %
1.77 %

average idle just for 1.77 % and observe for 58.65 % of
the time.

3 Simulation
Simulations of the produced schedules were carried out
for assessing the accuracy of the earth orientation parameters (EOP) and station coordinates. These largescale Monte Carlo simulations were performed using
VieVS (Pany et al., 2011). The clock accuracy was set
to an Allan standard deviation (ASD) of 1 × 10-14 at
50 min (Herring et al., 1990), and a white noise of 30 ps
was used. The refractive index structure constant of thetroposphere Cn was set to 1.8 × 10-7 m-1/3 with a scaleheight of 2 km (Nilsson et al., 2007). In total, several
tens of thousands of simulations were generated andanalyzed.

4 Correlation
After the session was observed, the students got an introduction of the correlation of VLBI sessions with theDistributed FX-style correlator (DiFX) (Deller et al.,2007) and a presentation of the correlation on the Vienna Scientific Cluster (VSC-3).
During this course the students had to work on exercises to calculate the expected data size, transfer timeand correlation time for AUA047. In order to enable
the students to get a brief insight into the procedureof correlation, the students had to develop a FX- anda XF-style correlator in MATLAB and to compare theprocessing times.

5 Analysis
The analysis was done with VieVS using the vgosDB
format. The students found and removed four clock
breaks at the station Yarragadee. Further, outlier detection was performed, shown in Figure 4.
The optimising analysis was done by each groupindependently based on their scientific goal. The students varied for example, zenith wet delay intervals,
constraints and the mapping functions. Finally, a session fit of 38.6 ps was achieved.

Fig. 4: Residuals in cm for AUA047 for all stations after removing clock breaks. Detected outliers, marked with a black cross, were

removed in a next step.

246

Wolf et al.

Fig. 5: Residuals in cm for AUA047 at station Hobart showing the effect of not considering the a priori model of solid earth tides.

To demonstrate the effect of a priori models likesolid earth tides, tidal atmospheric loading and tidal
ocean loading, the students investigated the residuals of
the analysis without including these models separately
and compared their results with the results obtained byapplying the models. Figure 5 shows the effect of solid
earth tides at station Hobart.

6 Conclusion
The official IVS session AUA047 was fully organized
by students at TU Wien. All necessary steps, including scheduling, large-scale Monte Carlo simulations,correlation and analysis were done by each group independently. This shows that both software packages,
VieSched++ and VieVS, are understandable and easy
to use. The students got an insight into VLBI throughthe practical tasks and exercises. Next to the successin university teaching this course delivered scientificresults as any other VLBI session does, like station coordinates and earth orientation parameters.

ReferencesBöhm J, Böhm S, Boisits J, et al. (2018) Vienna VLBI and Satellite Software (VieVS) for Geodesy and Astrometry. PASP,
130, 044503, doi:10.1088/1538-3873/aaa22b
Deller A T, Tingay S J, Bailes M, et al. (2007) DiFX: A software
correlator for very long baseline interferometry using multiprocessor computing environments. PASP, 119, 318–336,
doi:10.1086/513572
Herring T, Davis J, Shapiro I (1990) Geodesy by radio interferometry: The application of Kalman Filtering to the analysis
of very long baseline interferometry data. J Geophys Res,95, 12561–12581, doi:10.1029/JB095iB08p12561.
Nilsson T, Haas R, Elgered G (2007) Simulations of atmospheric path delays using turbulence models. Proc. 18th
EVGA Working Meeting, 175–180
Nothnagel A, Artz T, Behrend D, et al. (2017) International
VLBI Service for Geodesy and Astrometry. J Geod, 91,
711–721, doi:10.1007/s00190-016-0950-5
Pany A, Böhm J, MacMillan D, et al. (2011) Monte Carlo simulations of the impact of troposphere, clock and measurement
errors on the repeatability of VLBI positions. J Geod, 85,
39–50, doi:10.1007/s00190-010-0415-1
Plank L, Lovell J, McCallum J, et al. (2017) The AUSTRAL VLBI observing program J Geod, 91, 803–817,
doi:10.1007/s00190-016-0949-y
Schartner M, Böhm J (2019) VieSched++: A New VLBI
Scheduling Software for Geodesy and Astrometry. PASP,
131, 084501, doi:10.1088/1538-3873/ab1820

Comparison of Integrated GNSS LOD to dUT1
M. Mikschi, J. Böhm, S. Böhm, D. Horozovic

Abstract The problem of estimating the bias of Lengthof Day (LOD) data from Global Navigation Satellite
Systems (GNSS) is discussed. A method for estimating the bias is described and ideal parameters of themethod for the used data are given. The time correction
dUT1 is estimated using four different GNSS data sets
and the achieved results are presented and discussed.
For the best data set the root mean square error (RMSE)of the dUT1 estimate is 40 µs after 7 days and 60 µs after 14 days.

Keywords dUT1 · LOD · GNSS

1 Introduction
The time correction dUT1 is an important Earth orientation parameter that is regularly determined with
Very-Long-Baseline Interferometry (VLBI) intensive
sessions. While VLBI is the only technique that is capable of estimating dUT1 directly, its (negative) time
derivative, Length of Day (LOD), can be measured
with, among other techniques, a global GNSS network.
Therefore, it is possible to estimate dUT1 by integrating GNSS LOD values and adding the known dUT1
value at t0 .

Markus Mikschi · Johannes Böhm · Sigrid Böhm · Dzana Horozovic
Technische Universität Wien, TU Wien, Karlsplatz 13, AT-1040
Vienna, Austria(Correspondence: markus.mikschi@geo.tuwien.ac.at)

dUT 1(T ) =Z T−LOD(t)dt + dUT 1(t0 )

(1)

t0

However, GNSS LOD values contain a bias which
has to be accounted for in order to achieve good dUT1
estimates. This bias mainly stems from perturbationsof the GNSS orbits which cannot be differentiated fromchanges in the LOD estimates. Especially the effects ofsolar radiation pressure on the right ascension of theascending node are problematic.

2 Methods
Four different GNSS LOD data sets from Horozovic
and Weber (2018) are used for estimating dUT1. Twoof which consist solely of GPS data and two are calculated based on a combination of GPS and Galileo. For
both of these variants one and three day solutions with
one hour resolution are used. All of the data sets encompass the time frame from 1-JUL-2017 to 1-NOV2017, use the ECOM model and are referred to as
1D GPS, 3D GPS, 1D GPSGAL and 3D GPSGAL inthis paper. The data was processed with Bernese 5.2(Dach et al., 2015) using data from over 190 IGS stations. For both the calibration of the offset in the GNSSLOD data, as well as the integration constant the IERS
14C04 data set (Bizouard et al., 2018), hereafter referred to as C04, is used. Furthermore, it is also used
for the assessment of the estimated dUT1 values.
For the integration of the discrete LOD values thecumtrapz function in Matlab (R2016b) is used, whichapproximates the integral with trapezoids. A better approximation with integrating a cubic spline interpolation yields no significant improvements. In order to as247

248

sess the quality of the dUT1 estimates, the LOD values are integrated over a specific integration period andthe differences to the C04 dUT1 is calculated. Subsequently the integration window is shifted by one day
and the process is repeated as long as there is data available. Thereafter the computed differences to C04 arestacked as a function of t-t0 and the mean error as wellas the RMSE are calculated. In Figure 1 an example ofthis stacking can be seen. Each of the faint lines is thedifference between the estimated dUT1 for a specificintegration period and the C04 dUT1. Due to the shifting by one day, each LOD value contributes to multiple
integration periods and as a consequence some repeating patterns in the difference to C04 can be seen.

Fig. 1: Illustration of the stacking of integration periods and thebias estimation method.

The GNSS LOD data possesses an offset as is normal with this kind of data. Since dUT1 has to be known
at t0 it is sensible to assume that LOD is also knownat that time. Therefore the bias can be estimated as
the difference between the GNSS LOD and that known
LOD at t0 . However, the calculated LOD difference at
t0 does not represent the offset over the integration period due to the noisy nature of the LOD data. Applying
the same technique to smoothed GNSS LOD does notdeliver satisfying results either.
In order to overcome this problem, a period withcertain length prior to the integration start t0 is chosen as a calibration period. During this period the LOD
is integrated in a moving integration window and theresulting difference to C04 gets stacked as describedabove. Because the offset in the LOD data is approximately constant during an integration period, the cal-

Mikschi et al.

culated mean error of the dUT1 estimate drifts linearly.
Thus the offset can be estimated by fitting a linear function to the mean error and taking the slope as is illustrated in Figure 1.
For comparison, the IGS corrects for the LOD bias
by averaging the differences of the daily LOD values
from every analysis center of the past weeks from theactual LOD value determined by the IERS Rapid Service. This produces an analysis center specific LOD
bias which is used in the estimation (Kammeyer, 2000).

3 Results
Different parameters for the used calibration method
were tested in order to get the best dUT1 estimates.
Among them were weighted averaging of the different integration periods when calculating the mean error and different lengths for both the overall calibration
window and the integration period within that window.
The rational behind a weighted average of the different
integration periods is that more recent periods may be
more indicative of the current LOD offset. However,
it is found that the more equally the different periods
are weighted the better the calibration performs and anormal averaging yields the best results. It is important
to note that the used calibration method introduces aweighting of the LOD values by itself. This is because
the integration window is always completely containedin the calibration period and gets shifted by one day
each time. As a consequence the first and the last LOD
value contribute to one integration period, the secondand second last to two and so on.
For the calibration length 7, 14, 21, 28 and 35 day
periods were tested. Since the used calibration method
acts similar to a moving mean, the resulting LOD bias
signal gets smoother with a prolonged calibration period as can be seen in Figure 2. In order to achieve agood end result in terms of the RMSE as well as topreserve some of the bias variation a compromise of
21 days was chosen.
Concerning the length of the integration window
within the calibration period 3, 5, 7, 10 and 14 days
were tested, with 14 days resulting in the best calibration. For the following results a calibration with normal averaging, 21 day calibration period and 14 day
integration window was used.

Comparison of Integrated GNSS LOD to dUT1

Fig. 2: The estimated bias over time depending on the chosen

length of the calibration period.

249

constant over the integration period. However, this assumption particularly does not hold true for this data
set. Figure 4 shows the estimated biases for the different GNSS data sets over time. The bias for 1D GPS
has the biggest amplitude and very steep slopes, whichmakes it hard to estimate with the employed method.
Both the mean error and RMSE of all solutions exhibit some periodic behavior. This is partly due to thefact that the C04 dUT1 values have a temporal resolution of one day while the GNSS LOD data has a temporal resolution of one hour. In order to compare theestimated dUT1 with the C04 data the latter is linearlyinterpolated. In addition, the LOD data contains someresidual components of the ocean tides which were notremoved by the model used in Bernese 5.2 (Dach et al.,2015).

Using this configuration good dUT1 estimates canbe achieved. Figure 3 depicts the mean error and the
RMSE of the dUT1 estimates when compared to the
C04 as is described above. The calibration of the LOD
bias was successful to a certain degree, as the mean errors of all four data sets are approximately zero. The
three day solutions outperform the one day solutions
by a large margin. The addition of Galileo to GPS for
1D yields a much bigger improvement than for 3D,
for which the improvement is almost negligible. The
RMSE for the best data set, 3D GPSGAL, after sevendays is approximately 40 µs.

Fig. 4: The estimated bias for the four data sets over the different

integration periods.

Assuming the distribution of the differences between GNSS LOD and C04 LOD is symmetrical andhas an expectation value of zero, the RMSE follows
a true random walk error and is proportional to thesquare root of time:
RMS E ∝

Fig. 3: The mean error and RMSE for the four data sets as a(2)

Figure 7 shows the RMSE of the dUT1 estimatesover 7 days at the time-stamps of the C04 data. In addition the results of a curve fit offunction of t-t0 .

RMS E ≈ a ∗Part of the reason that the calibration fails for the
1D GPS dataset is that the offset is assumed to be√t − t0√t − t0 + d(3)

to these points is shown. The estimated parameters
as well as the goodness of fit (gof ) values are listed

250

Mikschi et al.

in Table 1. The offset parameter d would be zero in
an ideal case and the exhibited deviations from thattheoretical value are due to remaining biases in thecorrected GNSS LOD. These most likely stem fromorbital perturbations, mainly due to radiation pressure,which were not completely modeled by the used
ECOM model in Bernese 5.2 (Dach et al., 2015).
3D GPS and 3D GPSGAL follow the fitted function
quite well although their gof parameters are not particularly good. On the other hand 1D GPS has the best
gof parameters but exhibits a positive curvature after
day 3 which means that the RMSE does not truly follow a square root function. This is explored further in
the next section with a 14 day integration period.

Fig. 6: The mean error and RMSE for the four data sets as afunction of t-t0 for a longer integration window of 14 days.

imately 9 days. However, when looking at the trend of
their respective mean errors, it becomes clear that 3D
GPS profits of a much better bias estimation than 3D
GPSGAL. Since their RMSE are so similar it can beinferred that GPSGAL 3D has a lower scattering but
the bias is either not as constant as for the other data
sets, harder to be estimated or both. It is interesting tonote that bias estimation for GPS improves when goingfrom the 1D to the 3D solution but for GPSGAL it is
the other way around. The reasons for this have to beinvestigated.
Fig. 5: Result of fitting a square root function with an offset term

to the RMSE at the C04 sampling points.

Table 1: Fitting parameters and goodness of fit for 7 days

Data set
GPS 1DGPSGAL 1D
GPS 3DGPSGAL 3D

a
32.71
21.22
15.20
14.51

d
-1.70
2.56
3.56
2.68

R2
0.995
0.985
0.966
0.974

RMS
2.120
2.466
2.662
2.220

Figure 6 shows the progression of the mean error
and RMSE for an integration period of 14 days. The
1D GPS estimate is by far the worst and its RMSE increases linearly with time instead of the square root oftime. This means that the conditions of a pure random
walk error are not met, which is apparent when looking
at the trend of the respective mean error which is quite
significant. The already small advantage of 3D GPSGAL over 3D GPS pretty much vanishes after approx-

Figure 7 depicts the RMSE of the dUT1 estimatesover 14 days at the sampling points of the C04 data set
and the results of a curve fit according to Equation 3.
The parameters resulting from this fit are listed alongside the gof measurements in Table 2. In addition the
figure also shows a RMSE reference, which was takenfrom a paper about estimation of a dUT1-like quantitiybased on GPS orbit planes (Kammeyer, 2000). Withinthat paper the RMS change over time was investigatedover longer periods and the resulting RMS approxima√tion is given with 30µ s w wherein w is the elapsed
time in weeks.

Table 2: Fitting parameters and goodness of fit for 14 days

Data set
GPS 1DGPSGAL 1D
GPS 3DGPSGAL 3D

a
40.58
21.61
12.33
12.70

d
-12.04
2.70
7.77
5.30

R2
0.972
0.989
0.943
0.957

RMS
7.590
2.516
3.346
2.835

Comparison of Integrated GNSS LOD to dUT1

Fig. 7: RMSE over 14 days at C04 times and the curve fitting

results. Additionally a reference curve is shown.

Interestingly the estimate for the a parameter decreases quite drastically between the 7 and 14 day fits
for the two 3D solutions. The d parameter on the other
hand gets bigger. This points to disturbances of thepure random walk error that get absorbed in the a parameter in case of the 7 day fit, but move to the d termin the 14 day fit. The 1D GPS dUT1 estimate performs
even worse, has bad gof parameters and exhibits a positive curvature that is even more visible in Figure 7 thanit was in the previous ones.
Both 3D solutions perform similar, although a bit
worse than the reference data. However, this is due tothe sharp increase at the beginning of the integration
period. The actual course of the RMSE as described by
the a term is very similar with 12.33 and 12.70 compared to 11.34. The a term for the reference data results from a scaling of the weekly coefficient by √1 .
7
The reasons for the steep increase in the RMSE at thevery beginning of the integration period need to be investigated further.

4 Conclusions
The presented bias estimation method yields good results and enables to obtain usable dUT1 estimates. It
works best for the used 1D GPSGAL and 3D GPS data
sets while struggling with GPS 1D. Both 3D data setsyield good dUT1 estimates with the 3D GPSGAL doing so despite a slightly worse bias estimation based on
the mean error. 1D GPS results in the worst bias esti-

251

mation and the worst RMSE by a big margin. This ismost likely due to a higher variability of the bias during
a single integration period.
The best case RMSE after 7 days with the used data
is 40 µs with the 3D GPSGAL data set. After 14 days
the estimates based on 3D GPSGAL and 3D GPS are
nearly identical and exhibit an RMSE of almost 60 µs.
All those accuracy measures do not include the uncertainty of the initial dUT1 value at t0 . The attainable accuracy of dUT1 from VLBI intensive sessions is 20 µs
for the best global intensives (Schuh and Böhm, 2013)
and about 40 µs for European intensives (Schartner etal., 2018).
When comparing the obtained dUT1 RMSE to theaforementioned reference data set the former falls behind a bit. While the best GNSS data sets, 3D GPS
and 3D GPSGAL exhibit a similar a parameter forthe curve fit, the steep incline of the RMSE at the beginning and the accompanying high d value lead to aworse overall performance.

References
Kammeyer P (2000) A UT1-Like Quantity from Analysis of
GPS Orbit Planes. Celestial Mechanics and Dynamical Astronomy, 77, 241–272
Horozovic D, Weber R (2018) Bestimmung von hochfrequenten
Erdrorationsparametern unter Verwendung von GPS und
Galileo Beobachtungsdaten. In: Abstract Book Geodätische
Woche 2018
Dach R, Lutz S, Walser P, et al. (2015) Bernese GNSS Software Version 5.2. Astronomical Institute, University of Berndoi:10.7892/boris.72297 http://www.bernese.unibe.ch
Matlab, version R2016b (9.1.0.441655) The MathWorks Inc.
Schuh H, Böhm J (2013) Very long Baseline Interferometry for
Geodesy and Astrometry In: Guochang Xu (ed.): Sciences ofGeodesy II, Innovations and Future Developments, Springer
Verlag, ISBN 978-3-642-27999-7, doi:10.1007978-3-64228000-9, 339–376
Schartner M, Böhm J, Bolaño R, et al. (2018) VLBI Intensive
sessions on a European baseline for the estimation of dUT1;
GRA, 20, EGU2018-14986, EGU General Assembly 2018
Bizouard C, Lambert S, Gattano C, et al. (2019) The IERS EOP
14C04 solution for Earth orientation parameters consistent
with ITRF 2014. J Geod, 93, 621–633, doi10.1007/s00190018-1186-3

Combination of IVS Intensive Sessions – Approach, Benefit,
and Operability
S. Bachmann, D. Thaller, A. Girdiuk

Abstract In this contribution we present the status of
the intra-technique combination of VLBI intensive sessions for dUT1 estimation. So far, only 24h sessions areroutinely combined using the contributions of various
IVS Analysis Centers. We present our approach andfirst results to establish a combined IVS product for
intensive sessions based on datum-free normal equations. We applied a so called σ2 -approach to estimate
the individual weighting factor for each AC reflecting
the inner accuracy of the constituent and, consequently,
its contribution to the combined solution. The individual and the combined solutions are compared to dUT1
from IERS 14C04 series, where we found a WRMS of
26.6 µs for the combined solution and 32.8, 33.9, 34.6,
and 24.2 for the individual AC solution. An offset of
7.9 µs for the combined solution has been estimated.
Additionally, we compared the combined solution to
dUT1 as reported in the GSFC Intensives series andto the IVS Quarterly 24h combined EOP series. We
found an offset of −4.0 µs, a WRMS of 35.2 µs, anda RMS of 79.8 µs w.r.t. the GSFC series, and an offset
of 2.8 µs, a WRMS of 34.9 µs, and a RMS of 40.7 µs
compared to IVS Quarterly 24h series. Both comparisons show baseline-dependent statistics for the different INT networks (INT1, INT2, and INT3). Eventually,
we discuss the benefit of such a combined product aswell as the possibilities and challenges to install an operational IVS product.

Keywords Combination · Earth orientation parameters (EOP) · Intensives · UT1 · VLBI
Sabine Bachmann · Daniela Thaller · Anastasiia Girdiuk
Federal Agency for Cartography and Geodesy (BKG), RichardStrauss-Allee 11, DE-60598 Frankfurt am Main, Germany(Correspondence: sabine.bachmann@bkg.bund.de)

1 Motivation and objective
Combined VLBI products are well established in theInternational VLBI Service for Geodesy and Astrometry (IVS, Nothnagel et al., 2017) for station coordinates and Earth orientation parameter (EOP), given thata combined product shows improved statistics in comparison to a single individual solution (c.f. Böckmann
et al., 2010; Bachmann et al., 2016). Improving and expanding the range of combined products is one of thetasks of the IVS Combination Center. So far, only daily
24h sessions have been used to generate IVS combined
products. The aim of this study is to evaluate whether
IVS intensive 1h sessions (also called Intensives) benefit from a combination on a comparable level as 24h
sessions do, to carve out a combination approach and toevaluate the feasibility to establish an operational product.

2 Input contributions and combination
approach
In analogy to the combination approach for 24h sessions (see Bachmann et al., 2016), the Intensives combination is based on datum free normal equations provided in SINEX format. The contributions of various
IVS Analysis Centers (AC) are stacked to generate a
combined solution, as shown in Fig. 1.
The input SINEX files contain station coordinates,
pole coordinates and their rates, dUT1 and LOD. In
the first step, the parameters of all input contributions
are transformed to mid-session epochs. Additionally,
the station coordinates are transformed to equal a priori
station coordinates. The a priori station coordinates are
extracted from the most recent VLBI combined long252

IVS Intensives Combination
SINEX files- Station coordinates- X- and Y-Pole (+rates)- dUT1, LOD

253

AC1 ... ACn

Epoch transformation (mid-session)

Transformation on equala priori station coordinates

Datum application(fix station coordinates & pole)VTRF

X-, Y-Pole from IGS rapid

Individual solution

Outlier test dUT1
IVS
Data-

Weight estimation (σ2)

center

Accumulated combined solution

SINEX Combi

Outlier test EOP Combi

Fig. 1: Combination scheme for IVS intensive sessions

term solution VTRF, which is updated four times a year
to ensure up-to-date coordinates (see https://ccivs.bkg.
bund.de/index.php?uri=quarterly/vtrf for additional information). IVS Intensives are dedicated to provide
dUT1 values on a daily basis, which requires an extended east-west baseline. Due to this single baseline
configuration the estimable parameters of IVS Intensives are limited to dUT1. Errors in other EOPs, especially polar motion and nutation, propagate directly
into dUT1 as has been evaluated by, e.g., Nothnagel
and Schnell (2008). It is thus crucial to introduce theseparameters with high accuracy. Therefore X-, Y-pole,and LOD a priori values are introduced using IGS rapid
solutions for higher accuracy. Rapid IGS products havea 17-41 hours latency, which is generally sufficient for
IVS Intensives. In the next step, individual solutions foreach AC are generated to be used for an outlier test for
dUT1 and for the estimation of the weighting factors
for individual solutions. In contrast to a variance component estimation (VCE), which is applied for 24h sessions (see Bachmann et al. (2016) for further details),a σ2 -approach is applied to determine the individual
weighting factor w:

w=

1
σ2i

with i = 1 ... n(1)

This factor is then used in the combination of IVS
Intensives, where n is the number of contributing ACs
and σ2i is the a posteriori variance factor of the individual AC solution determined in the preceding step.
The last step is the accumulation of the datum freenormal equations using the individual weighting factors for each AC and to produce the combined solution, and a SINEX file containing the combined datum free normal equation, the appropriate variancecovariance matrix, and the estimates. The datum is applied likewise as for the individual solutions. The final step would be to provide the combined SINEX
file operationally to the IVS data center. Since too few
ACs provide Intensives on operational basis to have asufficient amount of SINEX files (>3), this step cannot be established at this time. For this study we included SINEX files available at the IVS data center,namely from AC BKG and USNO. Given the necessity to transform all contributions to the same a priori
station coordinates and EOP, SINEX files containing
solely dUT1 are therefore not suitable for our purposes.
Additionally, SINEX contributions from AC SHA andVIE provided on request are used. Altogether we included four contributions using two different software
packages. The input contributions comprise each typeof Intensives from 2017. Overall 258 equal sessions for
all ACs are used in this study.

3 Results of combination
In the following section we evaluate the results of the
combined dUT1 solution over a one year time spanin 2017. We are interested to see if our weighting approach is appropriate, i.e. it reflects the inner quality of
the contributing solutions, and if the combination candeliver an improved dUT1 product.

3.1 Weighting factor estimation
For IVS Intensives a VCE, using station coordinatesand EOP, cannot be applied as for 24h sessions, because of the the baseline configuration. Commonly, a
VCE is applied to define the accuracy relations between the constituents by distinguishing the individual variance components from the total variance. To
reproduce a relationship of the inner accuracy within

254

the Intensives combination, the σ2 -approach has beenchosen (see Sect. 2). First, external effects are minimized by introducing equal a priori values for station
coordinates and EOP, as well as transforming to equal
epochs (see Fig. 1). Individual solutions are calculated
and the resulting weighting factors are estimated eventually. The estimated weighting factors vary between
one and two with some peaks for two ACs. The meanvalues are 2.4 for BKG, 1.4 for SHA, 1.5 for USNO,
and 1.0 VIE, with some larger peaks reaching 19 at
the maximum. Subsequently, the reason for the peaks
is not yet clear and needs to be identified. Nevertheless, the individual weighting factors estimated using
the σ2 -approach provides reliable results reflecting theinner accuracy between the constituents appropriately.

3.2 dUT1 results
We are interested to see if IVS Intensives do have abenefit from a combination as 24h sessions do (seeBachmann et al., 2016). Since VLBI is the only space
geodetic technique having direct access to dUT1, finding appropriate external comparisons is challenging.
Hence, we compare our estimated dUT1 time-series on
a session-wise basis to the IERS 14C04 series, to the
IVS 24h Quarterly combined series, and to the EOP series provided by Goddard Space Flight Center (GSFC),
which is derived solely from Intensives. This series is
independent, because no SINEX files of this AC are
included in the combined solution.

Comparison to IERS 14C04

Figure 2 shows the dUT1 residuals from each of thecontributing ACs and the combined solution w.r.rt. theIERS 14C04 series (c.f. Bizouard et al., 2018). Slightoffsets are present for two ACs (see also Table 1), andslight irregularities between 2017.9 and 2018.0 are visible. Table 1 lists the WRMS, RMS, and the offset ofthe dUT1 time-series w.r.t. IERS 14C04 series. The
variability tends to attenuate for the combined solution.
Comparison to GSFC Intensives time series

The comparison to the GSFC Intensives series in Fig. 3
shows a scatter of the residuals of ±30 µs, with an offset
of −4.0 µs, a WRMS of 6.5 µs and a RMS of 46 µs. The

Bachmann et al.
Table 1: RMS and Offset for dUT1 w.r.t. IERS 14C04 series(258 equal sessions for each AC)
AC
RMS [µs] WRMS [µs] Offset [µs]
BKG
36.5
32.8
5.3
SHAO
37.1
33.9
8.1
USNO
38.2
34.6
11.0
VIE
33.4
24.2
2.1
COMBI
28.2
26.6
7.9

small scatter is due to the fact that both dUT1 values
are estimated from IVS Intensive series. When looking into sessions details, we see separation between the
Intensive observations: INT1 sessions shown as black
dots in Fig. 4, and INT2 sessions shown as red triangles in the same figure. INT1 sessions are observed
regularly Monday to Friday at 18:30h UTC between
stations Kokee Park (Hawaii, USA) and Wettzell (Germany). INT2 sessions are observed regularly on Saturday and Sunday at 7:30h UTC between stations Ishioka (Japan) and Wettzell (Germany), and INT3 sessions are observed regularly on Monday at 7:00h UTC
between stations Ishioka (Japan), Ny-Ålesund (Svalbard, Norway), and Wettzell (Germany). The latter isshown as blue squares in Fig. 3. Table 2 shows the offset, WRMS, and RMS for each of the INT observations. INT1 and INT2 show a comparable offset, butdifferences in the (W)RMS values due to the different
variability of the residuals. The influence of the baseline configuration on dUT1 estimation can be found in
Nothnagel and Schnell (2008). INT3 sessions show thelargest variations and offset due to its sparse observation, which results from few input contributions.
Table 2: Offset, WRMS, and RMS for dUT1 combined solution

w.r.t. GSFC Intensives series
INT series Offset [µs] WRMS [µs] RMS [µs] Nb. sessions
INT1
−6.2
27.0
79.8
208
INT2
−8.2
7.4
39.0
95
INT3
40.5
102.5
211.4
11
all
−4.0
35.2
79.8
314

Comparison to IVS Quarterly combined solution

The IVS Quarterly solution is a combined EOP series
using all IVS 24h sessions suitable for EOP determination, and is thus independent from IVS Intensives. Also
the nutation parameters are estimated, while for Intensives the nutation parameters need to be fixed to thea priori precession/nutation model (see Malkin (2011)

dUT1 differences w.r.t. IERS C04 [µ s]

IVS Intensives Combination

255

250
BKG
SHAO
USNO
VIE
COMBI

200
150
100
50
0
-50
-100
-150

-200
2017

2017.22017.42017.62017.820182017.62017.82018Year

dUT1 COMBI diff. w.r.t. GSFC series [μs]Fig. 2: dUT1 residuals w.r.t. IERS 14C04
200
150

INT1
INT2
INT3

100
50
0
-50
-100
-150
2017

2017.22017.4Year

Fig. 3: dUT1 residuals w.r.t. GSFC eopi series. INT1 sessions are shown as black points, INT2 sessions as red triangles, and INT3

sessions as blue squares

for details on the impact of the nutation on dUT1 estimation). IVS 24h dUT1 values are cubic spline interpolated to the Intensives session epochs using regularization functions (cf. Ch. 8 of IERS Conventions2010).

replacement for Ishioka-Wettzell due to IVS CONT17
activities). The influence of the baseline geometry on
dUT1 estimation is explained in Nothnagel and Schnell(2008).

Figure 4 shows the results of the differences to theinterpolated IVS 24h sessions. We observe a scatter ofthe residuals of about ±75 µs which is – as expected –larger than Intensives-only comparisons. The residuals
show an overall offset of 2.8 µs, a WRMS of 34.9 µs,
and a RMS of 40.7 µs, while the variations are smaller
w.r.t. each other, but larger compared to the GSFC series. Considering interpolation biases, introduced bysparse sampling points with gabs of up to 3.5 days,
the comparison to the IVS Quarterly solution shows
good results in the expected range. Comparable to the
GSFC comparison, we see clear differences in the offset for the different INT sessions (see Table 3). Additionally, we notice a session-dependent larger scatter after 2017.8 for INT2, that can be explained by abaseline change for those sessions (Seshan-Wettzell in

Table 3: Offset, WRMS, and RMS for dUT1 combined solution

w.r.t. IVS Quarterly solution
INT series Offset [µs] WRMS [µs] RMS [µs] Nb. sessions
INT1
−0.4
25.7
28.3
208
INT2
6.1
50.2
58.0
95
INT3
24.4
31.6
45.6
11
all
2.8
34.9
40.7
314

4 Conclusions
These first results show that combining individual IVS
Intensives is a considerable way to introduce an improved dUT1 product in terms of statistics. In comparison to the well-established IVS 24h rapid combined solution, we introduced an adapted combination method-

Bachmann et al.
dUT1 COMBI diff. w.r.t. IVS 24h [μs]

256
200
150

INT1
INT2
INT3

100
50
0
-50
-100
-150
2017

2017.22017.42017.62017.82018

Year

Fig. 4: dUT1 residuals w.r.t. IVS Quarterly 24h solution. INT1 sessions are shown as black points, INT2 sessions as red triangles,

and INT3 sessions as blue squares

ology for IVS Intensives with an appropriate weighting
strategy and datum application. The combined dUT1
results show an offset of 7.9 µs, an RMS of 28.2 µs,
and a WRMS of 26.6 µs w.r.t. the IERS 14C04 series.
Comparing to the GSFC Intensives series, the overall
offset is −4.0 µs, and the WRMS and RMS are 35.2 µs
and 79.8 µs, respectively. The comparison to the IVS
24h Quarterly series show an overall offset of 2.8 µs, a
WRMS and a RMS of 34.9 µs and 40.7 µs, respectively.
But there is a clear dependency on the specific INT(INT1, INT2, and INT3) sessions visible. So far, onlya small number of IVS ACs are currently analyzing
and submitting Intensive SINEX files operationally. Including more AC contributions (esp. from divers software packages) is thus highly desired in the near future. Then, adjusting a weighting strategy considering
different software packages can be envisaged, comparably to the process used in the 24h combination (seeBachmann et al. (2016) for details). The objective is toestablish an operational combined IVS Intensive product (depending on availability of individual AC contributions and achievable latency).
We thank our colleagues from Shanghai Observatory, US Naval Observatory, and Vienna University ofTechnology for providing SINEX files, which allowed

us to set up the combination process and to carry out
these first investigations.

References
Bachmann S, Thaller D, Roggenbuck O, et al. (2016) IVS
contribution to ITRF2014.
J Geod, 90(7):631–654,
doi:10.1007/s00190-016-0899-4
Bizouard C, Lambert S, Gattano C, et al. (2018) The IERS EOP
14C04 solution for earth orientation parameters consistent
with ITRF2014. J Geod, 93:621–633, doi:10.1007/s00190018-1186-3
Böckmann S, Artz T, Nothnagel A, et al. (2010) International VLBI service for geodesy and astrometry: Earth orientation parameter combination methodology and qualityof the combined products. J Geophys Res, 115(B04404),
doi:10.1029/2009JB006465
Malkin Z (2011) The impact of celestial pole offset modellingon VLBI UT1 intensive results. J Geod, 85(9):617–622,
doi:10.1007/s00190-011-0468-9
Nothnagel A, Schnell D (2008) The impact of errors inpolar motion and nutation on UT1 determinations fromVLBI Intensive observations. J Geod, 82(12):863–869,
doi:10.1007/s00190-008-0212-2
Nothnagel A, Artz T, Behrend D, et al. (2017) International VLBI Service for Geodesy and Astrometry - Delivering high-quality products and embarking on observations of the next generation. J Geod, 91(7):711–721,
doi:10.1007/s00190-016-0950-5

Comparison of VLBI-based Luni-solar Nutation Terms
V. Puente, J. Y. Richard, M. Folgueira, N. Capitaine, C. Bizouard

Abstract In this work, nutation time series determinedby several International VLBI Service for Geodesy
and Astrometry (IVS) analysis centers are compared interms of corrections to luni-solar nutation terms. Different VLBI-based series of celestial pole offsets areused as input for a least-square harmonic fitting of corrections to nutation terms.

Keywords Earth rotation · Nutation · VLBI

The purpose of this contribution is to compare thedifferences between the celestial pole offsets from different VLBI-based series consistent in terms of software configuration. Series provided by the International VLBI Service for Geodesy and Astrometry (IVS,
Nothnagel et al., 2017) and combined solutions areanalysed. The celestial pole offsets series from eachsource are used as pseudo-observations for a leastsquare harmonic fitting to obtain different corrections
to nutation terms.

1 Introduction

2 Theoretical background

Very Long Baseline Interferometry (VLBI) is the only
space geodesy technique that can directly observe thecelestial pole offsets. These values are time-dependent
corrections to the IAU200A/2006 nutation and precession model that are estimated by different VLBI analysis centres. The celestial pole offsets, together with therest of Earth Orientation Parameters (EOP) are combined by the IERS and disseminated in official series.
Vı́ctor Puente
National Geographic Institute of Spain, General Ibañez de Ibero
3, ES-28003, Madrid, Spain
Marta Folgueira
Department Section of Astronomy and Geodesy, Faculty ofMathematics, University Complutense of Madrid, ES-28040
Madrid, Spain
Jean-Yves Richard · Nicole Capitaine · Christian Biozuard
SYRTE, Observatoire de Paris, PSL Research University, CNRS,
Sorbonne Universités, UPMC Univ. Paris 06, 61 avenue del’Observatoire, FR-75014, Paris, France(Correspondence: vpuente@fomento.es)

The Earth Orientation Parameters constitute the key input for the coordinate transformation between the Geocentric Celestial Reference System (GCRS) and International Terrestrial Reference System (ITRS). These
parameters are the components of the polar motion (xP ,yP ), the difference UT1-UTC and the celestial pole offsets (dX, dY) with respect to IAU200A/2006 nutationand precession model.
From VLBI-based series of celestial pole offsets(dX, dY), it is possible to perform a least-square harmonic fit of the main luni-solar nutation terms of the
IAU2000A model:

dX =
dY =

42
X
i=1
42
X

areal,i cos(ARGi ) + aimag,i sin(ARGi ),(1)
areal,i sin(ARGi ) + aimag,i cos(ARGi ),

i=1

257

258

Puente et al.

where ARGi are linear combinations (multipliers
factor ki in Table 2) of the fundamental arguments(Fi ) of the luni-solar nutation theory IERS Conventions(2010):
ARGi = ki,1 F1 + ki,2 F2 + ki,3 F3 + ki,4 F4 + ki,5 F5F1 = 134.96340251◦ + 1717915923.2178”t+31.8792”t2 + 0.051635”t3 − 0.00024470”t4 ,F2 = 357.52910918 + 129596581.0481”t◦−0.532”t2 + 0.000136”t3 − 0.00001149”t4 ,F3 = 93.27209062◦ + 1739527262.8478”t(2)−12.512”t2 − 0.001037”t3 + 0.00000417”t4,
F4 = 297.85019547◦ + 1602961601.2090”t−6.706”t2 + 0.006593”t3 − 0.00003169”t4 ,F5 = 125.04455501◦ − 6962890.5431”t+7.4722”t2 + 0.007702”t3 − 0.00005939”t4 ,where t is measured in Julian centuries of TDB.
Table 1 includes the list of the 42 nutation harmonic
terms to be fitted. Columns ki correspond to the multiplier factor of Delaunay arguments shown in Equation 2.

3 Software analysis
Table 2 presents a summary of the estimation strategies of the IVS analysis centers whose products areused in this work. This information is available at IVS
servers. Solutions not using ICRF2 as celestial frameor not using IAU200A/2006 nutation and precession
model have been excluded of the analysis.

4 Results
The corrections to IAU 2000A model were computedby means of a least-square harmonic fitting after having
removing Free Core Nutation (FCN) effect using B16
model Belda et al. (2016).
This FCN model is based on the following equations:
XFCN = AC cos(σFCN t) − AS sin(σFCN t) + X0 ,YFCN = AS cos(σFCN t) + AC sin(σFCN t) + Y0 ,(3)where A is the amplitude, t is the time since J2000.0
expressed in days, P is the period (=430.0027 solardays), σFCN = 2π/P is the frequency of FCN and X0
and Y0 are constant offsets. A sliding window of 400
days and a step of one day was used to fit a FCN modelfor each solution analysed, i.e. the set of VLBI-based
solutions aforementioned and also two series of combined solutions: IVS and EOP 14 C04 Bizouard et al.
(2019).
Analysed time span was restricted to 1993-2019,
since data before 1993 has poorer precision and temporal resolution Belda et al. (2016). Median amplitudes of
the corrections to IAU 2000A model and the range between the values are shown in Figure 1 and comparedto the results reported by Yao (2013) and Gattano et al.
(2017). It should be noted that in Gattano et al. (2017)
all IVS solutions were used regardless their configuration, using data starting from 1984. For Yao (2013), thefitted amplitudes correspond to an individual solution,
so there is no figure for the range.
Table 3 includes a statistical summary of the differences between the amplitudes obtained in this workand the ones obtained by Yao (2013) and Gattano etal. (2017). These differences are computed removing
the FCN signal — column w/o FCN — and without
removing the FCN model — w/ FCN—. The results
show a better agreement between the different solutions for areal amplitudes than for aimag ; and removing the FCN signal (median differences below 0.4 µas).
These results were also confirmed by an ANOVA analysis.

5 Conclusions and outlook
A comparison of the differences between corrections to
the principal nutations of the IAU 2000A model havebeen computed based on celestial pole offsets from different VLBI-based series. The results show in general agood agreement with similar studies on this topic. Disagreement with Gattano’s results for the longest nutation periods are probably due to the different set-up of
the analysis: different set and time span of IVS solutions and different model to remove the FCN signal.
In the future, it is expected to enrich this analysis
with GNSS-based estimation of celestial pole offsets
Puente et al. (2018). This would be a valuable contribution to the study of short-period nutation terms.

VLBI-based Luni-solar Nutation Terms

References
Belda S, Ferrándiz J M, Heinkelmann R, et al. (2016) Testing a
new Free Core Nutation empirical model. J Geodyn, 94-95,
59–67
Bizouard C, Lambert S, Gattano C et al. (2019) The
IERS EOP 14C04 solution for Earth orientation parameters consistent with ITRF 2014. J Geod, 93(5),621–633,
doi:10.1007/s00190-018-1186-3
Gattano C, Lambert S B, Bizouard C (2017) Observation of the
Earth’s nutation by the VLBI: how accurate is the geophysical signal. J Geod, 91(7), 849–856, doi:10.1007/s00190016-0940-7
IERS Conventions (2010) In: G. Petit, B. Luzum (eds.) IERS
Technical Note 36, Frankfurt am Main: Verlag des Bundesamts für Kartographie und Geodäsie,
Nothnagel A, Artz T, Behrend D, et al. (2019) International
VLBI Service for Geodesy and Astrometry - Deliveringhigh-quality products and embarking on observations of thenext generation. J Geod, 91(7), 711–721
Puente V, Capitaine N, Richard J Y, et al. (2018) Nutation determination by means of GNSS: status and prospects. 20th
EGU General Assembly
Yao K (2013) Estimation de la nutation de la Terre par les techniques VLBI et GPS. Thesis at University Pierre and Marie
Curie.

259
Table 1: Harmonic terms and corresponding periods of luni-

solar nutation.
i ki,1 ki,2 ki,3 ki,4 ki,5 Period (days)
1
0 0 0 0 1
−6798.38
20 0 0 0 −1
6798.38
30 0 0 0 2−3399.19
40 0 0 0 −23399.195
2 0 −2 0 −2
−1615.75
6 −2 0 2 0 21615.75
7
2 0 −2 0 −1
−1305.48
8 −2 0 2 0 11305.48
9
2 0 −2 0 0−1095.18
10 −2 0 2 0 01095.18
11 0 −1 0 0 −1−386.00
12 0 1 0 0 1
386.00
13 0 −1 0 0 0−365.26
14 0 1 0 0 0
365.26
15 0 −1 0 0 1−346.64
16 0 1 0 0 −1
346.6417 0 0 −2 2 −2−182.62
18 0 0 2 −2 2
182.6219 0 −1 −2 2 −2−121.75
20 0 1 2 −2 2
121.7521 1 0 0 −2 0
−31.81
22 −1 0 0 2 031.81
23 −1 0 0 0 0−27.5524 1 0 0 0 027.55
25 −1 0 −2 2 −2
−23.9426 1 0 2 −2 2
23.94
27 0 0 0 −2 0
−14.7728 0 0 0 2 014.77
29 −2 0 0 0 0−13.7830 2 0 0 0 0
13.78
31 0 0 −2 0 −2
−13.6632 0 0 2 0 2
13.66
33 1 0 −2 −2 −2−9.56
34 −1 0 2 2 2
9.56
35 −1 0 −2 0 −2
−9.13
36 1 0 2 0 2
9.13
37 −1 0 −2 0 −1
−9.12
38 1 0 2 0 1
9.12
39 0 0 −2 −2 −2−7.10
40 0 0 2 2 2
7.10
41 −2 0 −2 0 −2
−6.86
42 2 0 2 0 2
6.86

260

Puente et al.

Table 2: Estimation strategies of different IVS solutions analysed.

Analysis center
BKG
GSF
IAA
OPA
USN
Software package
Calc 10.0/Solve Calc 11.0/Solve OCCAM/GROSS Calc 11.0/Solve Calc 11.0/Solve
Celestial frame
ICRF2
ICRF2
ICRF2
ICRF2
ICRF2
Terrestrial frame
ITRF08
ITRF14
ITRF14
ITRF14
ITRF14
IERS Conventions
2010
2010
2006
2010
2010
Nutation/precession model IAU200A/2006 IAU200A/2006 IAU200A/2006 IAU200A/2006 IAU200A/2006
Estimation model
Least squares Least squares Kalman filter
Least-squares Least-squares
Troposphere
VMF1
VMF1
VMF1
VMF1
VMF1

50

50
GattanoPuenteasas

GattanoPuente
Yao

0

-50

0

-50
0

5

10

15

20

25

30

35

40

0

50

5

10

15

20

25

30

40

50
GattanoPuenteas

GattanoPuente
Yao

as

35

0

-50

0

-50
0

5

10

15

20

25

30

35

40

0

5

10

15

20

25

30

35

40

Fig. 1: Comparison of the median and range of the amplitudes with respect to Yao (2013) and Gattano et al. (2017).

VLBI-based Luni-solar Nutation Terms

261

Table 3: Statistical summary of the differences in the computed

corrections to IAU 2000A.
Period(days)

Puente vs. Yao
Puente vs. Gattano
areal
aimag
areal
aimag
w/o
w/ w/ow/ w/ow/ w/ow/
FCN FCN FCN FCN FCN FCN FCN FCN−6798.38 −35.9 14.0 −2.7 19.2 −44.6 11.6 −11.4 16.8
6798.38 −4.4 38.3 −14.7 15.8 −8.4 36.3 −18.7 13.8
−3399.19 −9.0 0.0
1.9 −2.8 −9.0 4.1
1.9 1.3
3399.19
7.7 5.6 16.2 −10.2 −3.7 5.6
4.8 −10.2−1615.75 −1.8 2.6
1.1 5.7 −1.0 1.2
1.9 4.3
1615.75
1.0 3.6 −6.1 4.4
1.7 4.1 −5.4 4.9−1305.48
4.8 3.9
5.4 2.3
0.9 6.4
1.5 4.81305.48 −3.2 −0.5 −0.1 −1.3 −1.4 −4.6
1.7 −5.4−1095.18 −4.9 −2.5 −8.3 −7.5 −4.2 1.5 −7.6 −3.5
1095.18
8.7 3.4 11.6 5.6
3.7 2.6
6.6 4.8−386.00
1.2 −1.1 10.2 −3.1 −3.1 4.0
5.9 2.0
386.001.2 −3.4
2.5 −3.2
0.6 −4.0
1.9 −3.8−365.26 23.5 −16.7 14.7 −5.4 −2.3 −18.1 −11.1 −6.8
365.26 −1.1 8.1 −0.9 8.3 −1.3 2.0 −1.1 2.2−346.64 −2.1 8.5 −5.6 5.4
9.1 −3.7
5.6 −6.8
346.64
1.2 −4.7
3.7 −2.6
0.8 0.0
3.3 2.1−182.62 −2.6 3.5 −3.2 3.9
1.3 4.8
0.7 5.2
182.62
2.4 −4.2
2.3 −5.8 −0.4 −1.0 −0.5 −2.6
−121.75
0.1 −1.3 −1.0 1.0
1.0 −3.1 −0.1 −0.8
121.75 −2.7 −1.9 −2.7 −2.3 −0.8 −2.4 −0.8 −2.8
−31.81
1.7 −1.0
2.7 −0.
0.5 0.4
1.5 1.3
31.81
1.8 2.9
1.5 1.7
0.4 −1.0
0.1 −2.2−27.550.3 −4.4
1.6 −4.7
1.5 0.5
2.8 0.2
27.55 −0.8 −4.4 −0.7 −4.4
1.7 −0.4
1.8 −0.4−23.94
1.2 −2.5
1.3 −2.1
1.5 1.6
1.6 2.0
23.94 −0.3 0.1
0.3 1.2 −0.6 −1.0
0.0 0.1−14.77 −0.4 −1.0 −0.2 −0.5
0.7 −1.3
0.9 −0.8
14.77 −4.4 1.8 −4.7 1.4
0.0 0.2 −0.3 −0.2
−13.780.1 −1.5 −1.3 −3.2
2.1 −0.4
0.7 −2.1
13.78
1.3 −2.3
2.0 −1.3 −0.8 1.5 −0.1 2.5−13.66
7.2 3.5
7.0 0.6
3.5 1.2
3.3 −1.7
13.66
3.1 −0.2
4.8 −0.4
1.5 −0.3
3.2 −0.5−9.56
1.6 −1.0
0.1 −1.0 −1.5 −1.9 −3.0 −1.9
9.56
1.1 1.2
1.7 −1.7 −0.9 0.8 −0.3 −2.1
−9.13
2.0 −2.4
3.7 −3.4
0.2 0.5
1.9 −0.5
9.13
3.3 0.6
1.9 0.5 −0.1 0.4 −1.5 0.3−9.12 −2.3 −0.8 −1.5 −1.0 −1.5 −1.6 −0.7 −1.8
9.12 −2.3 −4.0 −2.7 −2.0 −0.1 0.4 −0.5 2.4−7.10 −2.0 −2.8 −5.3 −1.0
0.3 1.0 −3.0 2.8
7.10 −10.6 5.4 −7.5 7.4 −0.8 −1.3
2.3 0.7−6.86 −5.1 2.5 −7.0 0.7 −0.9 0.8 −2.8 −1.0
6.86 −2.9 1.8 −3.5 −0.4
0.4 1.0 −0.2 −1.2
MedianUnit in µas

0.1 −0.3

0.2 −0.7 −0.0

0.4

0.4 −0.3

Index of authors

Aktas R., 87, 143
Albo Castaño C., 22
Alef W., 27, 31, 103, 107
Ambrosini R., 47
Amils Samalot R., 22
Anderson J. M., 107
An T., 94
Araña V., 67
Azcue E., 71, 199, 234
Böhm J., 42, 119, 124, 180Bérubé M., 177
Bachem J., 87, 143
Bachmann S., 252
Baldominos Delgado A., 22
Balidakis K., 204
Barbas Calvo L., 22
Barbieri E., 87, 143
Bautista Durán M., 22
Baver K. D., 157, 224
Beltrán Martı́nez F. J., 22
Bernhart S., 103, 107, 124, 129
Bezrukovs V., 31
Bianco G., 47
Bizouard C., 257
Bolaño R., 1
Bolotina O., 224
Bolotin S., 224
Bortolotti C., 47
Botha R. C., 162
Brandl M., 124, 129
Bregolin F., 52
Brunini C., 124
Byram S., 152Böhm J., 162, 167, 243, 247
Böhm S., 247
Calonico D., 47, 52
Campbell R. M., 112
Cantoni E., 52
Capitaine N., 257
Carlin L., 87, 143

Carter M. S., 184
Casey S., 5
Cerretto G., 52
Charlot P., 112, 219
Chen L., 148
Chen W., 134, 138
Chin Chuan L., 229
Chu Z., 57
Clivati C., 47, 52
Collioud A., 219
Combrinck W. L., 162
Conway J., 5
Corbin A., 194
Cordobés D., 67
Cui L., 134
Dı́ez González M., 22
Davis M., 152, 184
de Vicente P., 1, 22, 107
de Wild R., 31
de Witt A., 138, 162, 209, 238
Dieck C., 152, 184
Domı́nguez Cerdeña I., 67
Dornbusch S., 27, 31
Dorta P., 67
Elgered G., 5, 75
Engelhardt G., 189
Eschelbach C., 17, 172
Eskelinen J., 84
Fan Q., 12
Fey A., 214
Flygare J., 31
Folgueira M., 257
Gómez González J., 67
Gómez Molina G., 22
Gómez Espada Y., 71, 199, 234
Gómez M. E., 112
Gallego J. D., 22, 31
Garcı́a A., 67

263

264

Garcı́a Carreño P., 22
Garcı́a Pérez O., 22
Garcia-Espada S., 1, 71, 199, 234
Gipson J., 152, 157, 224
Girdiuk A., 189, 252
González Garcı́a J., 22, 107
Gordon D., 209, 214, 224, 238
Greiwe A., 17
Gruber J., 42, 162, 243
Gulyaev S., 138
Guo S., 12
Haas R., 5, 17, 27, 75, 107, 194
Hachisu H., 52
Hameed M. S., 87, 143
Hammargren R., 5
Hankey W., 243
Han S., 134
Hargreaves J., 31
Hase H., 124
Helldner L., 5
He X., 148
Himwich E., 177
Horozovic D., 247
Huang Y., 57
Hunt L., 214
Ichikawa R., 52
Ido T., 52
Ishigaki M., 138
Ishijima H., 52
Ivanov D., 138
Jacobs C. S., 162, 209, 238
Jiang W., 148
Jingyao S., 87, 143
Johansson K.-Å., 5, 27
Johnson M., 152, 214

Index of authors

Le Bail K., 209, 224
Liu C., 12
Liu L., 62, 94
Liu Q., 57
Li J., 12
Li P., 57Lösler M., 17, 172Müskens A., 103, 107, 124
Maccaferri G., 47, 52
MacMillan D., 152, 157, 224
Malo Gómez I., 22
Martı́ Vidal I., 107
Matsumoto S., 80
Ma L., 134, 148
McCallum J., 138, 229, 243
McCallum L., 138, 229, 243
Melnikov A., 138
Mikhailov A., 138
Mikschi M., 247
Munekane H., 80
Mura A., 47, 52
Müskens A., 167
Näränen J., 84
Nalbach M., 31
Namba K., 52
Nanni M., 47
Natusch T., 138
Negusini M., 47, 52
Neidhardt A., 87, 124, 129, 143
Nemitz N., 52
Nickola M., 162
Nilsson T., 204
Ning T., 204
Nosov E., 37
Nothnagel A., 42, 107, 167
Okamoto Y., 52

Kareinen N., 84
Kasemann C., 31
Kawai E., 52
Keimpema A., 112
Kettenis M., 112
Komuro J., 52
Kondo T., 62
Krásná H., 162, 238
Kravchenko E., 47
Kronschnabl G., 124, 129
Kurihara S., 80
Kylenfall U., 5López Fernández I., 22López Fernández J. A., 1, 22, 67López Pérez J. A., 22, 31, 67
López Ramasco J., 22, 71
Lambert S., 138
La Porta L., 27, 103, 107, 124, 129
Levi F., 47, 52

Pérez I., 67
Pantaleev M., 31
Patino Esteban M., 22
Perini F., 47, 52
Pettersson L., 5, 75
Phogat A., 124Ping J., 134
Pizzocaro M., 52
Plötz C., 107, 124, 129, 167, 189
Poutanen M., 84
Prudencio A., 71
Puente V., 71, 199, 234, 257
Ricci R., 47, 52
Richard J. Y., 257
Riepl S., 172
Roma M., 47
Rottmann H., 27, 103, 107
Roy A. L., 27, 31

Index of authors

Salarpour S., 229
Salguero F., 124
Santamaria L., 47
Santos A., 1
Savolainen T., 107
Schönberger M., 87, 143
Schüler T., 103, 107, 124, 129
Schartner M., 42, 119, 138, 162, 167, 180, 243
Schoonderbeek G. W., 31
Schwarz W., 124, 129
Schüler T., 172
Sekido M., 52
Serna Puente J. M., 22
Shabala S., 229
Shu F., 12, 57, 62, 134, 138, 148
Siciliani de Cumis M., 47
Small D., 107
Soja B., 138, 238
Spitzak J., 214
Stagni M., 47
Stamatakos N., 184
Sun J., 134
Szomoru A., 87, 143
Takahashi R., 52
Takefuji K., 52
Tangen L. M., 10
Tercero Martı́nez F., 22, 31
Thaller D., 189, 252
Ticay J., 67
Titov O., 138
Tong F., 62
Tong L., 62
Tsutsumi M., 52
Tuccari G., 27, 31
Ueshiba H., 80

265

Ujihara H., 52
Ullrich D., 189
Umei M., 80
Valdés M., 71, 234
Vaquero Jiménez B., 22
Vera J., 124
Wagner J., 27, 103, 107
Wahlbom J., 75
Wakasugi T., 80, 116
Wang G., 12
Wang J., 12
Wang L., 12
Wennerbäck L., 5, 75
Weston S., 138
Wojdziak R., 189
Wolf H., 243
Wunderlich M., 27, 31
Xia B., 138
Xu Z., 57
Yang X., 12, 148
Yiang Y., 12
Yi S. O., 138
Yu L., 12
Zhang H., 12
Zhang J., 62, 94
Zhang X., 12
Zhao D., 12
Zhao R., 12
Zheng W., 62, 94
Zheng X., 57
Zubko N., 84

This page is intentionally left blank.

Program of the EVGA 2019
Sunday, March 17
Icebreaker reception

Register, get your badge, meet your friends, have 19:00-21:00
fun!

Monday, March 18
Rafael Robaina Romero (Rector of Opening ceremony of the EVGA 2019
Las Palmas University); José Antonio López-Fernández (Astronomy,
Geophysics and Space Applications
Subdirector at IGN); Rüdiger Haas
(EVGA Chair)

09:00-09:30

Session 1.1
O101 José Antonio López-Fernández

09:30-10:30, chair: Gino Tuccari
The current status of RAEGE

09:30-09:45

O102 Rüdiger Haas

Status of the Onsala twin telescopes

09:45-10:00

O103 Leif Morten Tangen

Status for the establishment of a new fundamental 10:00-10:15
site in Ny-Ålesund

O104 Jinling Li

The Sheshan 13-m radio telescope

10:15-10:30

coffee break

10:30-11:00

Session 1.2
O105 Michael Lösler

11:00-12:00 chair: Evgeny Nosov
Measuring focal-length variations of VGOS- 11:00-11:15
telescopes using unmanned aerial systems

O106 Pablo de Vicente

Instrumentation developed for VGOS at IGN 11:15-11:30
Yebes Observatory

O107 Gino Tuccari

DBBC3 towards the BRAND EVN receiver

O108 Walter Alef

BRAND - A wideband receiver for astronomy and 11:45-12:00
geodesy”stretch your legs” breakAppendix-A Page-1

11:30-11:45

12:00-12:15

Session 1.3
O109 Evgeny Nosov

12:15-13:15 chair: Pablo de Vicente
The stability of delay in VLBI digital backends

O110 Jakob Gruber

A simulator to generate VLBI baseband data in 12:30-12:45
MatlabO111 Roberto Ricci

Optical fiber links used in VLBI networks and 12:45-13:00
remote clock comparisons: the LIFT/MetGesp
project

O112 Mamoru Sekido

Italy-Japan broadband VLBI experiment for opti- 13:00-13:15
cal clock comparison

lunch break

12:15-12:30

13:15-14:15

Session 1.4
O113 Xin Zheng

14:15-15:15 chair: Walter Alef
Researching and application of VLBI differential 14:15-14:30
phase delay in lunar exploration

O114 Walter Brisken

Status and development plans of the VLBA

14:30-14:45

O115 Aard Keimpema

Recent technical developments at JIVE

14:45-15:00

O116 Tetsuro Kondo

Comparison of results between CVN and K5 soft- 15:00-15:15
ware correlators”stretch your legs” break

15:15-15:30

Session 2.1
O201 Laura La Porta

15:30-16:30 chair: Aletha de Witt
The Bonn Correlation Center and VGOS

15:30-15:45

O202 Walter Alef

The EU-VGOS project

15:45-16:00

O203 Maria Eugenia Gomez

Implementation of a geodetic path at the JIVE cor- 16:00-16:15
relator

O204 Takahiro Wakasugi

Activity report on the Asia-Oceania VLBI Group 16:15-16:30(AOV)

Session 2.2
O205 Aletha de Wittcoffee break

16:30-17:00

17:00-18:00 chair: Laura La Porta
The Southern VLBI Operations Centre

17:00-17:15

Appendix-A Page-2

O206 Matthias Schartner

Results with the scheduling software VieSched++ 17:15-17:30

O207 Christian Plötz

INT9 - dUT1 determination between the geodetic 17:30-17:45
observatories AGGO and Wettzell

O208 Torben Schüler

LCONT18 - The local continuous measurement 17:45-18:00
campaign at Wettzell of 2018

Poster session

Look at all the nice posters!

18:00-19:30

Tuesday March 19
Session 2.3
O209 Jing Sun

09:00-9:45 chair: Torben SchülerPreliminary work on promoting radar astronomi- 09:00-09:15
cal study

O210 Oleg Titov

Observations of radio sources near the Sun

O211 Alexander Neidhardt

Autonomous observations of VLBI radio tele- 09:30-09:45
scopes”stretch your legs” break

09:15-09:30

09:45-10:00

Session 3.1
O301 Dan MacMillan

10:00-10:45 chair: Arthur Niell
Analysis of EOP and scale from the simultaneous 10:00-10:15
CONT17 networks

O302 Johannes Böhm

CONT17 from a VieVS perspective

O303 Maria Davis

The IERS Rapid Service / Prediction Center UT1- 10:30-10:45
UTC combined solution: Present and future Contributions

coffee break

10:15-10:30

10:45-11:15

Session 3.2
O304 Anastasiia Girdiuk

11:15-12:00 chair: Dan MacMillan
Analysis of regular and specific intensive sessions 11:15-11:30

O305 Armin Corbin

Scheduling of twin telescopes and the impact on 11:30-11:45
troposphere and UT1 estimation

Appendix-A Page-3

O306 Arthur Niell

VLBI tie between the KOKEE12M and KO- 11:45-12:00
KEE20M antennas”stretch your legs” break

12:00-12:15

Session 3.3
O307 Axel Nothnagel

12:15-13:15 chair: Johannes Böhm
Gravitational deformation investigations and their 12:15-12:30
impact on global telescope coordinates: The Onsala 20 m radio telescope caseO308 John Gipson

Gravitational deformation of VLBI antennas and 12:30-12:45
the impact on the TRF

O309 Matthias Glomsda

Impact of non-tidal loading in VLBI analysis

O310 Kyriakos Balidakis

How does geophysical loading affect Earth rota- 13:00-13:15
tion? Simulations and reality

lunch break
Session 3.4
O311 Vı́ctor Puente

12:45-13:00

13:15-14:15

14:15-15:15 chair: Axel Nothnagel
Comparison of troposphere delays from GNSS 14:15-14:30
and VLBI in R1 and R4 sessions

O312 Periklis-Konstantinos Diamantidis Comparison of tropospheric delay estimation us- 14:30-14:45
ing VLBI CONT14 data and WVR for the Onsala
station
O313 Tobias Nilsson

An assessment of the tropospheric parameters es- 14:45-15:00
timated from the CONT17 campaign

O314 Frédéric Jaron

An analytical VLBI delay formula for Earth satel- 15:00-15:15
lites”stretch your legs” break

15:15-15:30

Session 3.5
O315 Grzegorz Klopotek

15:30-16:15 chair: John Gipson
Geodetic VLBI observations of lunar radio 15:30-15:45
sources – Current status and recommendations for
future researchO316 Benedikt Soja

Ionospheric calibration for K-band celestial refer- 15:45-16:00
ence frames

O317 Karine Le BailTime stability of the K-band catalog sources

Appendix-A Page-4

16:00-16:15

coffe break

16:15-16:45

Session 3.6
O318 Patrick Charlot

16:45-17:45 chair: Karine Le BailICRF3, the new realization of the International 16:45-17:00
Celestial Reference Frame

O319 James M. Anderson

Toward imaging 3000+ ICRF sources from clo- 17:00-17:15
sure quantities from 1979–present

O320 Lucas Hunt

VLBA Imaging of ICRF 3 sources

17:15-17:30

O321 Arnaud Collioud

The Bordeaux VLBI Image Database (BVID)

17:30-17:45”stretch your legs” break

17:45-18:00

Session 3.7
O322 Ming Hui Xu

18:00-19:00 chair: Patrick Charlot
Structure effects in broadband VGOS data

O323 Sergei Bolotin

The source structure effect in broadband observa- 18:15-18:30
tions

O324 Simin Salarpour

Source structure effects in the next-generation of 18:30-18:45
VLBI observations

O325 Leonid Petrov

Remaining problems in geodesy / astrometry 18:45-19:00
VLBI and approaches to their solutions

Rüdiger Haas

18:00-18:15

Closing remarks

19:00-19:15

EVGA dinner

19:15-23:59

Appendix-A Page-5

Posters
Session 1
P101 David Cordobés

Status of the future RAEGE radio telescope at Gran Canaria

P102 Andrea Prudencio

First steps in gravitational deformation modeling of the VLBI Yebes radio
telescopes

P103 Gunnar Elgered

The Onsala Tide Gauge Station: Experiences from the first three years ofoperation

P104 Hiroshi Munekane

VLBI-GNSS collocation survey at the Ishioka VLBI station

P105 Nataliya Zubko

Progress and current status on VGOS project at the Metsähovi Geodetic
Research Station

P106 Alexander Neidhardt

Centralized monitoring of VLBI antennas for seamless auxiliary data

P107 Alexander Neidhardt

Remote access to the NASA Field System via Web browser

P108 Weimin Zheng

Space low-frequency radio observatory and the Earth-moon VLBI experiment

P109 Ahmad Jaradat

An artificial radio signal for VLBI satellite tracking

Session 2
P201 Xuan He

Mixed-mode VLBI observations with Chinese stations in APSG40

P202 Christopher Dieck

Intensive sessions with the Mauna Kea VLBA Station

P203 Dirk Behrend

Roll-out status of the VGOS network

P204 Hayo Hase

Argentinean-German Geodetic Observatory (AGGO)

P205 Karen BaverThe effect of source flux catalog latency on IVS-INT01 schedulingP206 Marisa Nickola

HartRAO local tie measurements: VLBI and ground survey

P207 Matthias Schartner

Impact of different observing rates on geodetic results

P208 Matthias Schartner

In-depth analysis of schedules optimized for certain VLBI experiments
using VieSched++

P209 Michael Lösler

A modified approach for process-integrated reference point determination

P210 Fengchun Shu

High sensitivity astrometry with the AOVAppendix-A Page-6

P211 Jakob Gruber

Vienna correlation activities

P212 Ed Himwich2018 IVS Network Performance

P213 Dhanya G. Nair

GMVA image database at 86 GHz now online

P214 Juan Zhang

The progress of CVN Software correlator and its applications

Session 3
P301 Andreas Hellerschmied Vienna VLBI Analysis Center (VIE)
P302 Christopher S. Jacobs

The X/Ka-band 2019a celestial frame:

P303 Esther Azcue

VLBI analyses at the National Geographic Institute of Spain

P304 Hana Krásná

Earth orientation parameters estimated from K-band VLBA measurements

P305 Helene Wolf

AUA047: Students at TU Wien organize their own VLBI session

P306 Aletha de Witt

The K-band (24 GHz) Celestial Reference Frame

P307 Markus Mikschi

Comparison of integrated LOD values from GNSS and AAM to dUT1
from VLBI

P308 Niko Kareinen

Simulated combined effect of extended source structure and baseline geometry to geodetic parameters estimated with VLBI

P309 Sabine Bachmann

Combination of IVS intensive sessions ’ approach, benefit, and operability

P310 Susanne Lunz

Radio source position offsets among various radio frames and Gaia

P311 Suxia Gong

Comparison of ionospheric delays between VLBI and GNSSP312 Tuomas Savolainen

NT-VGOS - Mitigating the source structure errors in the VGOS era

P313 Simona Di TomasoInter-comparison of GNSS and VLBI tropospheric parameters at colocated sites in Italy

P314 Vı́ctor Puente

Comparison of VLBI-based series of celestial pole offsets

P315 Ming Hui Xu

Comparison between time series of closure analysis and source positions
since 1980

P316 Svetlana Mironova

Diurnal and sub-diurnal EOP variations from VLBI global solution

Appendix-A Page-7

List of participants EVGA 2019
Name

Affiliation and Email address

Alef, Walter

Max Planck Institute for Radio Astronomy, MPIfR, Germany
walef@mpifr-bonn.mpg.de
Technische Universität Berlin, TU Berlin/German Research Centre for Geosciences,
GFZ, Germany
anderson@tu-berlin.de
Las Palmas de Gran Canaria University, ULPGC, Spainvarana@dsc.ulpgc.es
Instituto Geográfico Nacional, IGN, Spaineazcue@fomento.es
Bundesamt für Kartographie und Geodäsie, BKG, Germany
sabine.bachmann@bkg.bund.de
German Research Centre for Geosciences, GFZ, Germany
kyriakos.balidakis@gfz-potsdam.de
NVI, Inc., USA
dirk.behrend@nviinc.com
NASA/Jet Propulsion Laboratory, JPL, California Institute of Technology, USA
Konstantin.V.Belov@jpl.nasa.gov
Instituto Geográfico Nacional, IGN, Spainmabenito@fomento.es
Technische Universität Wien , TU Wien, Austria
johannes.boehm@tuwien.ac.at
NVI, Inc., USAsergei.bolotin@nasa.gov
Laboratoire d’Astrophysique de Bordeaux, France
geraldine.bourda@u-bordeaux.fr
National Radio Astronomy Observatory, NRAO, USAwbrisken@nrao.edu
Laboratoire d’Astrophysique de Bordeaux, France
patrick.charlot@u-bordeaux.fr
Yunnan Observatories, Chinese Academy of Science, China
chenwen@ynao.ac.cn
Laboratoire d’Astrophysique de Bordeaux, France
arnaud.collioud@u-bordeaux.fr
Joint Institute for VLBI ERIC, JIVE, The Netherlands
colomer@jive.eu
Chalmers University of Technology, Sweden
armin.corbin@chalmers.se
Instituto Geográfico Nacional, IGN, Spaind.cordobes@oan.es
U.S. Naval Observatory, USNO, USAmaria.a.davis33.civ@mail.mil
Yebes Observatory/Instituto Geográfico Nacional, IGN, Spain
p.devicente@oan.es

Anderson, James M.

Araña Pulido, Victor
Azcue, Esther
Bachmann, Sabine
Balidakis, Kyriakos
Behrend, Dirk
Belov, Konstantin
Benito, Marı́a ÁngelesBöhm, Johannes
Bolotin, Sergei
Bourda, Geraldine
Brisken, Walter
Charlot, Patrick
Chen, Wen
Collioud, Arnaud
Colomer, Francisco
Corbin, Armin
Cordobés Gallo, David
Davis, Mariade Vicente, Pablo

Appendix-A Page-8

de Witt, Aletha

South African Radio Astronomy Observatory, SARAO, South Africa
alet@hartrao.ac.za
Di Tomaso, Simona
E-GEOS ASI, Italysimona.ditomaso@e-geos.it
Diamantidis, Periklis-K.
Chalmers University of Technology, Sweden
periklis.diamantidis@chalmers.se
Dieck, Christopher
U.S. Naval Observatory, USNO, USAchristopher.dieck@navy.mil
Domı́nguez Cerdeña, Itahiza Instituto Geográfico Nacional, IGN-Canarias, Spain
ifdominguez@fomento.es
Dutka, Michael
U.S. Naval Observatory, USNO, USA
mdutka@cpi.com
Elgered, Gunnar
Chalmers University of Technology, Sweden
gunnar.elgered@chalmers.se
Eschelbach, CorneliaFrankfurt University of Applied Sciences/Laboratory for Industrial Metrology, Germany
cornelia.eschelbach@fb1.fra-uas.deEskelinen, Joona
Finnish Geospatial Research Institute, FGI, Finland
joona.eskelinen@nls.fi
Garcı́a Castellano, Abel
Instituto Geográfico Nacional, IGN, Spainabel.garcia@oan.es
Garcia-Espada, Susana
RAEGE Santa Maria-Azores/Instituto Geográfico Nacional, IGN, Spainsgespada@fomento.es
Gipson, John
NVI, Inc., USA
john.gipson@nviinc.com
Girdiuk, Anastasiia
Bundesamt für Kartographie und Geodäsie, BKG, Germany
anastasiia.girdiuk@bkg.bund.de
Glomsda, Matthias
Deutsches Geodätisches Forschungsinstitut, Technische Universität München, DGFITUM, Germany
matthias.glomsda@tum.deGómez, Maria Eugenia
Laboratoire d’Astrophysique de Bordeaux, France
maria.gomez@u-bordeaux.fr
Gómez Espada, Yaiza
Instituto Geográfico Nacional, IGN, Spain
becario.yge@fomento.esGómez González, Jesus
Instituto Geográfico Nacional, IGN, Spain
jggonzalez@fomento.es
Gong, Suxia
German Research Centre for Geosciences, GFZ, Germany
susia201507@gmail.com
González Matesanz, Javier Instituto Geográfico Nacional, IGN, Spainfjgmatesanz@fomento.es
Gruber, Jakob
Technische Universität Wien , TU Wien, Austria
jakob.franz.gruber@geo.tuwien.ac.atHaas, Rüdiger
Chalmers University of Technology, Sweden
rudiger.haas@chalmers.se
Haftings, Phillip
U.S. Naval Observatory, USNO, USA
phillip.haftings@navy.mil
Hall, David
U.S. Naval Observatory, USNO, USA
daveh922@verizon.net

Appendix-A Page-9

Hao, Longfei
Hardin, Matthew

Hase, Hayo
He, XuanHellerschmied, Andreas
Himwich, Ed
Huang, Yidan
Hunt, Lucas
Jaradat, Ahmad
Jaroenjittichai, Phrudth
Jaron, Frédéric
Johnson, Megan
Kareinen, Niko
Keimpema, Aard
Kirkvik, Ann-Silje
Klopotek, Grzegorz
Kondo, Tetsuro
Kotary, Nancy
La Porta, Laura
Lanotte, Roberto
Le Bail, Karine
Li, JinlingLösler, Michael

Yunnan Observatories, Chinese Academy of Science, China
haolongfei@ynao.ac.cn
Universities Space Research Association, USRA/U.S. Naval Observatory, USNO,
USA
mhardin42@gmail.com
Bundesamt für Kartographie und Geodäsie, BKG, Germany - Argentina
hayo.hase@bkg.bund.deShanghai Astronomical Observatory, SHAO, Chinese Academy of Science, China
hexuan@shao.ac.cn
Federal Office of Metrology and Surveying, Austria
andreas.hellerschmied@bev.gv.at
NVI, Inc., USA
ed.himwich@nviinc.com
Shanghai Astronomical Observatory, SHAO, Chinese Academy of Science, China
hyd@shao.ac.cn
U.S. Naval Observatory, USNO, USA
lucas.hunt@navy.mil
Institute of Geodesy and Geoinformation, Bonn University, Germanys7ahjara@uni-bonn.de
National Astronomical Research Institute, Thailand
phrudth@gmail.com
Institute of Geodesy and Geoinformation, Bonn University, Germany
jaron@igg.uni-bonn.de
U.S. Naval Observatory, USNO, USA
megan.johnson@navy.mil
Finnish Geospatial Research Institute FGI, Finland
niko.kareinen@nls.fi
Joint Institute for VLBI ERIC, JIVE, The Netherlands
keimpema@jive.nl
Norwegian Mapping Authority, NMA, Norway
ann-silje.kirkvik@kartverket.no
Chalmers University of Technology, Sweden
grzegorz.klopotek@chalmers.se
Shanghai Astronomical Observatory, SHAO, Chinese Academy of Science, China
kondo@shao.ac.cn
MIT Haystack Observatory, USA
nwk@mit.edu
Reichert GmbH/ Bundesamt für Kartographie und Geodäsie, BKG, Germany
laporta@mpifr-bonn.mpg.de
E-GEOS ASI/Space Geodesy Center, CGS, Italyroberto.lanotte@e-geos.it
NVI, Inc., USA
karine.lebail@nasa.gov
Shanghai Astronomical Observatory, SHAO, Chinese Academy of Science, China
jll@shao.ac.nc
Frankfurt University of Applied Sciences/Laboratory for Industrial Metrology, Germany
michael.loesler@fb1.fra-uas.deAppendix-A Page-10

López Fernández, Jose
L’Orange, Simon
Lunz, Susanne
Ma, Langming
MacMillan, Dan
Merkowitz, Stephen
Mikschi, Markus
Munekane, Hiroshi
Negusini, Monia
Neidhardt, Alexander

Nickola, Marisa
Niell, Arthur
Nilsson, Tobias
Nosov, Evgeny
Nothnagel, Axel
Petrov, LeonidPlötz, ChristianPorcas, Richard
Puente, Vı́ctor
Raut, Shrishail
Ricci, Roberto
Salarpour, Simin
Sandmo, TrondSargent, Andrew

Instituto Geográfico Nacional, IGN, Spainjalfernandez@fomento.es
Norwegian Mapping Authority, NMA, Norway
simon.lorange@kartverket.no
German Research Centre for Geosciences, GFZ, Germany
susanne.lunz@gfz-potsdam.de
National Time Service Center, Chinese Academy of Sciences, China
malm@ntsc.ac.cn
NVI, Inc., USA
dan.macmillan@nviinc.com
NASA/Goddard Space Flight Center, USA
stephen.m.merkowitz@nasa.gov
Technische Universität Wien , TU Wien, Austria
markus.mikschi@geo.tuwien.ac.at
Geospatial Information Authority of Japan, Japan
munekane-h96nu@mlit.go.jp
National Institute of Astrophysics, INAF-IRA, Italy
negusini@ira.inaf.it
Technische Universität München, TUM, Forschungseinrichtung Satellitengeodaesie,
Germany
neidhardt@fs.wettzell.deSouth African Radio Astronomy Observatory, SARAO, South Africa
marisa@hartrao.ac.za
MIT Haystack Observatory, USAaniell@mit.edu
Lantmäteriet, Sweden
jan-tobias.nilsson@lm.se
Institute of Applied Astronomy, Russian Academy of Sciences, IAA RAS, Russia
nosov@iaaras.ru
Institute of Geodesy and Geoinformation, Bonn University, Germany
nothnagel@uni-bonn.de
NASA/Goddard Space Flight Center, USA
Leonid.Petrov@nasa.gov
Bundesamt für Kartographie und Geodäsie, BKG, Germany
christian.ploetz@bkg.bund.de
Max Planck Institute for Radio Astronomy, MPIfR, Germany
porcas@mpifr-bonn.mpg.de
Instituto Geográfico Nacional, IGN, Spainvpuente@fomento.es
Technische Universität Berlin, TU Berlin, Germany
shrishail.raut@campus.tu-berlin.de
National Institute of Astrophysics, INAF-IRA, Italy
ricci@ira.inaf.it
University of Tasmania, Australia
simin.salarpour@utas.edu.au
Norwegian Mapping Authority, NMA, Norway
trond.sandmo@kartverket.no
U.S. Naval Observatory, USNO, USA
andrew.j.sargent@navy.mil
Appendix-A Page-11

Savolainen, Tuomas

Aalto University Metsahovi Radio Observatory, Finlandtuomas.k.savolainen@aalto.fi
Schartner, Matthias
Technische Universität Wien , TU Wien, Austria
matthias.schartner@geo.tuwien.ac.at
Schott Guilmault, Vladimir Centre National d’Estudes Spatiales, CNES, France
schottguilmault@ipgp.fr
Schuh, Harald
German Research Centre for Geosciences, GFZ, Germany
schuh@gfz-potsdam.de
Schüler, Torben
Geodetic Observatory Wettzell, Germany
gow@mailbox.org
Sekido, Mamoru
National Institute of Information and Communications Technology, NICT, Japansekido@nict.go.jp
Shu, Fengchun
Shanghai Astronomical Observatory, SHAO, Chinese Academy of Science, China
sfc@shao.ac.cn
Soja, Benedikt
Jet Propulsion Laboratory, JPL, California Institute of Technology, USA
bsoja@jpl.nasa.gov
Sun, Jing
National Astronomical Observatory, China
sunjing@bao.ac.cn
Sust, Eberhard
MT Mechatronics, Germany
eberhard.sust@mt-mechatronics.deTangen, Leif Morgen
Norwegian Mapping Authority, NMA, Norway
leif.morten.tangen@kartverket.no
Titov, Oleg
Geoscience Australia, Australiaoleg.titov@ga.gov.au
Tuccari, Gino
National Institute of Astrophysics, INAF-IRA/Max Planck Institute for Radio Astronomy, MPIfR, Italy
tuccari@mpifr-bonn.mpg.de
Valdés, Marcelino
Instituto Geográfico Nacional, IGN, Spainmvaldes@fomento.es
Verkouter, Harro
Joint Institute for VLBI ERIC, JIVE, The Netherlands
verkouter@jive.eu
Wakasugi, Takahiro
Geospatial Information Authority of Japan, Japan
wakasugi-t96kg@mlit.go.jp
Wolf, Helene
Technische Universität Wien , TU Wien, Austria
helene.wolf@geo.tuwien.ac.at
Xu, Ming Hui
Huazhong University of Scinece and Technology, China
mhxu@shao.ac.cn
Yang, Ying
National Time Service Center, Chinese Academy of Sciences, China
xiyinghe1@163.com
Zhang, Juan
Shanghai Astronomical Observatory, SHAO, Chinese Academy of Science, Chinazhangjuan@shao.ac.cn
Zheng, Weimin
Shanghai Astronomical Observatory, SHAO, Chinese Academy of Science, China
zhwm@shao.ac.cn
Zheng, Xin
Shanghai Astronomical Observatory, SHAO, Chinese Academy of Science, Chinazhengxin@shao.ac.cn
Zubko, Nataliya
Finnish Geospatial Research Institute, FGI, Finland
nataliya.zubko@nls.fi

Appendix-A Page-12

3rd IVS Training School on VLBI for
Geodesy and Astrometry

The participants of the 3rd IVS Training School on VLBI for Geodesy and Astrometry, heldat the University of Las Palmas de Gran Canaria, 14–16 March 2019

Appendix-B Page-1

The 3rd IVS Training School on VLBI for Geodesy and Astrometry, held at the Universityof Las Palmas de Gran Canaria, 14–16 March 2019. There were 54 registered participants, outof 23 were ”real students”, i.e. participants who are still in educational programs (Bachelor,
Master, or PhD), and 31 ” senior students”, i.e. senior scientists and post-docs. The participants
came from institutions worldwide, see Tab. 1.
Table 1: Number of participants and country codes of their home institutions.

ES US CN DE AT NO SE AU FI FR SA TH NL
12 11 8 7 4 4 2 1 1 1 1 1 1The school was meant to cover the complete ”VLBI chain”, from scheduling, observations,correlation and fringe fitting to data analysis. Twelve teachers were active in the school, see
Tab. 2, giving one lecture each. The lectures were complemented with 4 exercises that aimed
at using the acquired knowledge somehow in practical application. Also real observations
with the two VGOS antennas RAEGYEB and ONSA13NE were performed as part of the
VLBI school.
The complete program of the VLBI school is given in Table 3. The teaching material isavailable on the evga webpage under www.evga.org. All lectures were filmed, too, and thefilms can be made available on request.
The LOC took very good care of the participants and the teachers. There were regularcoffee breaks, and lunches. At the last day, the school ended with the VLBI school dinner in anice restaurant on the country side, including music and dance.

Table 2: Teachers and lecture topics.

Axel Nothnagel (AN) Intro Geodesy
Alet de Witt (AdW)
Intro Astrometry
Patrick Charlot (PC)Radio Sources
Gunnar Elgered (GE) Telescopes/Feeds/Receivers
Harro Verkoputer (HV) Data acquisition and transport
Gino Tuccari (GT)
Digital Backends
John Gipson (JG)
Scheduling
Walter Brisken (WB)
Correlation and fringe fittingRüdiger Haas (RH)
Fringe fitting/Fourfit
Dan MacMillan (DMM) Geophysical modelling
Johannes Böhm (JB)
Signal propagation
Sergei Bolotin (SB)
Data analysis

Appendix-B Page-2

Table 3: Program of the 3rd IVS school on VLBI.

Day-1, Thursday, 14 March 201908:50-09:00 Welcome and practical information (Susana Garcia-Espada + Rüdiger Haas)
09:00-09:45 L01: Why do we do it? A motivation for VLBI for Geodesy and Geosciences (AN)09:45-10:00 – Stretch your legs break –10:00-10:45 L01: – continued (AN)10:45-11:15 – Coffee break –11:15-12:00 L02: Why do we do it? A motivation for VLBI for Astrometry (AdW)
12:00-12:15 – Stretch your legs break –12:15-13:00 L02: – continued (AdW)
13:00-14:00 – Lunch break –14:00-14:45 L03: What do we observe? Radio sources (PC)14:45-15:00 – Stretch your legs break –15:00-15:45 L03: – continued (PC)15:45-16:00 – Coffee break –16:00-16:45 L04: What do we use to observe? VLBI stations, radio telescopes, receivers (GE)
16:45-17:00 – Stretch your legs break –17:00-17:45 L04: – continued (GE)
17:45-18:00 – Stretch your legs break –18:00-19:00 EX-1: Exercises on technical aspects (GE)Day-2, Friday, 15 March 201909:00-09:45 L05: How do we store and transport the data? Data acquisition and transport (HV)09:45-10:00 – Stretch your legs break –10:00-10:45 L05: continued (HV)10:45-11:15 – Coffee break –11:15-12:00 L06: How do we sample data? Digital backends (GT)
12:00-12:15 – Stretch your legs break –12:15-13:00 L06: continued (GT)
13:00-14:00 – Lunch break –14:00-14:45 L07: How do we plan observations? Scheduling (JG)
14:45-15:00 – Stretch your legs break –15:00-15:45 L07: continued (JG)
15:45-16:15 – Coffee break –16:15-17:00 EX-2: Exercises on scheduling (JG)
17:00-17:15 – Stretch your legs break –17:15-18:00 L08: How do we determine delays? Correlation and fringe-fitting (WB)
18:00-18:15 – Stretch your legs break –18:15-19:00 L08: continued (WB)
19:00-19:15 – Stretch your legs break –Appendix-B Page-3

19:15-20:00 L09: How do we determine group delays? Fringe-fitting with FourFit (RH)
Day-3, Saturday, 16 March 201909:00-09:45 EX-3: Exercise on correlation with DiFX and fringe-fitting with Fourfit (WB + RH)
09:45-10:00 – Stretch your legs break –10:00-10:45 EX-3: continued (WB + RH))
10:45-11:15 – Coffee break –11:15-12:00 L10: How do we model observations? Geophysical modeling (DMM)
12:00-12:15 – Stretch your legs break –12:15-13:00 L11: How do we model observations? Signal Propagation (JB)
13:00-14:00 – Lunch break –14:00-14:45 L12: How do we analyze the data? Data analysis for geodesy (SB)14:45-15:00 – Stretch your legs break –15:00-15:45 L12: continued (SB)
15:45-16:00 – Coffee break –16:00-16:45 EX-4: Exercise on data analysis (SB)16:45-17:15 – Stretch your legs break –17:15-18:00 EX-4: continued (SB)
20:00-23:59 – VLBI school dinner –After the IVS training school on VLBI, the participants were asked to evaluate the event.
About 50 % of the participants gave their feedback. Detailed results and answers from theevaluation are given in the next Section. In short, the probably five most important lessons
from this evaluation can be summarized as:• In general, the participants increased their knowledge in VLBI, i.e. they learnt something.
• The ’hands on’ exercises were appreciated, and should be intensified in future schools.
• There is a strong interest to participate in future IVS VLBI schools.
• The IVS VLBI school should be held more often than every 3rd year.
• The IVS VLBI school should be longer than 3 days.

Appendix-B Page-4

Evaluation of the 3rd VLBI school
To evaluate the 3rd IVS training school on VLBI for Geodesy and Astrometry, a questionnaire
was sent to all participants. This questionnaire was split into two parts of 10 questions each.
Part-I was closely related to the actual lectures and exercises and tried to measure whether
there was a learning experience. We received answers to the questions of Part-I by 25 of theparticipants. Part-II was also giving the opportunity to give feedback in text form, and here 29
participants answered.
The 20 questions were:
1. How much of a general overview about VLBI for Geodesy and Astrometry did/do you
have before/after the VLBI school?
2. What was/is your knowledge about radio sources before/after the VLBI school?
3. What was/is your knowledge about technical equipment at VLBI stations?
4. What was/is your knowledge about data sampling and data transport before/after the VLBI
school?
5. What was/is your knowledge about scheduling VLBI experiments before/after the VLBI
school?
6. What was/is your knowledge about correlation and fringe fitting before/after the VLBI
school?
7. What was/is your knowledge about geophysical modeling, including signal propagation
before/after the VLBI school?
8. What was/is your knowledge about VLBI data analysis before/after the VLBI school?
9. The lectures: What is your impression on the lectures that we had during the VLBI school?
10. The exercises: What is your impression on the exercises that we did during the VLBI
school?
11. What was BEST with the VLBI Training school? What did you like most?
12. What was WORST with the VLBI Training school? What did you dislike most ?
13. Are there any topics that you were missing? If so, which?
14. Would you be interested in attending another VLBI school in the future?
15. In case you wanted to attend another VLBI school in the future, would you be willing to
pay a special participation fee?
16. What is your opinion on how often the IVS should organise VLBI trainings schools?
17. Do you have suggestions on how to improve the VLBI school? If so, please indicate how?
18. What is your educational background?
19. If relevant, how many years have you been active in VLBI?
20. Any more feedback from your side?

Appendix-B Page-5

Q1: How much of a general overview about VLBI for Geodesy and Astrometry did/doyou have?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
BEFORE the school
2
4
14
4
1
77
AFTER the school
5
17
3
0
0
102

Q2: What was/is your knowledge about radio sources?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
BEFORE the school
4
4
8
6
3
75
AFTER the school
9
5
10
1
0
97

Q3: What was/is your knowledge about technical equipment at VLBI stations?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
BEFORE the school
0
4
7
10
4
61
AFTER the school
6
7
11
0
1
92

Q4: What was/is your knowledge about data sampling and data transport?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
BEFORE the school
1
3
10
5
6
63
AFTER the school
5
9
6
3
1
86

Appendix-B Page-6

Q5: What was/is your knowledge about scheduling VLBI experiments before/after the
VLBI school?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
BEFORE the school
2
4
8
8
3
69
AFTER the school
3
12
9
1
0
92

Q6: What was/is your knowledge about correlation and fringe fitting?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
BEFORE the school
0
3
7
7
8
55
AFTER the school
2
9
9
2
3
80

Q7: What was/is your knowledge about geophysical modeling, including signal propagation?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
BEFORE the school
2
8
9
5
1
80
AFTER the school
5
12
7
1
0
96

Q8: What was/is your knowledge about VLBI data analysis?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
BEFORE the school
4
10
4
5
2
84
AFTER the school
5
15
2
2
1
96

Appendix-B Page-7

Q9: The lectures: What is your impression on the lectures that we had during the VLBI
school?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
L01
12
12
1
0
0
111
L02
8
15
2
0
0
106
L03
8
12
5
0
0
103
L04
11
11
2
1
0
107
L05
10
13
1
1
0
107
L06
5
14
5
1
0
98
L07
8
13
4
0
0
104
L08
6
15
3
0
1
100
L09
7
10
6
0
1
94
L10
8
13
4
0
0
104
L11
8
11
6
0
0
102
L12
0
9
7
5
4
71

Q10: The exercises: What is your impression on the exercises that we did during the
VLBI school?
P
VERY GOOD GOODOK
BAD VERY BAD(5 points) (4 points) (3 points) (2 points) (1 point) points
EX-1
3
9
10
3
0
87
EX-2
4
11
9
1
0
93
EX-3
6
9
9
0
1
94
EX-4
2
6
9
3
5
72

Q11: What was BEST with the VLBI Training school? What did you like most?
• Meet lots of people who are experts in this field and learn from them. Also meet people
from any place in the world who is starting to work in this field.
• Practical exercises.
• The corresponding exercises were BEST, and I like most them.
• Data analysis and exercise.
• Exercises - I liked the fact we were 3-4 in a group and could work TOGETHER.
• Meeting very interesting people.
• Interaction, exercise part.
• Technical knowledge of the speakers.
• Learning the complete overview of the field.
Appendix-B Page-8

• Exercise sessions.
• The exercises.
• Data acquisition and transport and Digital backends.
• The opportunity to learn and review all VLBI topics.
• The complete coverage from the observation to the analysis.
• Talking with other people during coffee breaks.
• Meeting the right people. Those who have lot of VLBI experience along all the steps of
VLBI.
• A summary of the most important aspects of VLBI in ”only” 3 days, given by the top international experts. Hands-on experience with REAL data employing state-of-the-art software. Feedback from VLBI specialists. Mentimeter was very nice!
• The hands on parts were probably the most useful.
• The people, they were very nice and interesting.
• Practical Tasks.
• Meeting people, L01, L02.
• The location and people.
• Understanding which are the problems and how to resolve them, and see what is the VLBI
state of the art.
• The order of the talks, good introduction talks, a clear simplification of some of the specifictalks.
• Exercise.
• Organization of lectures, interaction with experts on fundamental level.
• Introduction by Prof. Nothnagel.
• Exercises.
• The practicality of teaching in particular areas.
Q12: What was WORST with the VLBI Training school? What did you dislike most?
• It should be at least 1 day more, it was too good but too short!
• Some days were just too long. Hard to stay concentrated.
• Unfamiliar content, such as radio , etc., I have very little harvest because the teacher taught
too fast.
• I think the worst part is the nusolve part. he did not explain nusolve clearly• Some of the presentations had too much theory and no application• Some speeches were a little bit rough• Not really• The analysis session was quite messy• Hands-on sessions where the number of server accounts are limited to 10, so, 3 or 4
students have to share• Stretch legs breaks without coffee!
• Nothing• Data analysis for geodesy
Appendix-B Page-9

• Too long days.
• The time was too short to understand everything - may be a personal problem ;-)• Analysis exercise and talk and too many many lectures during one day• The schedule was too tight. I would prefer not to have lecture exercises after 5 pm if
possible.
• The days were too long. 8 or 9 hours a day is the most one can generally handle it was toshort, i would prefer more time to improve my skills• EX-3, L12, EX-4
• VLBI data analysis part was bad• Students hadn’t slides beforehand to look figure details closer. You could put them at a
local server just at the beginning of the lesson• Exercises, practice part
• It was a bit too much intensive for 3 days.
• Analysis• NA• Maybe it could be done over more days
Q13: Are there any topics that you were missing? If so, which?
• Radio emission• Yes? more information or progress about Spacecraft Geodetic VLBI
• No
• Not really
• No
• No
• CRF, TRF• The topic I was more interested was data analysis and I couldn’t understand anything• Topics related to station operations.
• –• I would love to see more analysis and analysis background and a bit less technical details.Ê
• I would like something more about analysis and vlbi processing.
• Global solution and multi-technique combination, a summary of what are the most important issues that impede progress in VLBI - perhaps one slide from every lecturer• None• More detailed explanations of the basics• Field system, pre-check routines• In my opinion, all the relevant aspects were covered there.Ê
• Analysis methods, step between fringe fitting and group delays analysis• AIPS or Difmap or CASA data processingÊ
• NO
• no
• NA
Appendix-B Page-10

Q14: Would you be interested in attending another VLBI school in the future?
yes 27
no 2

Q15: In case you wanted to attend another VLBI school in the future, would you be
willing to pay a special participation fee?
yes 22
no 7

Q16: What is your opinion on how often the IVS should organise VLBI trainings schools?

every year every 2nd year every 3rd year every 4th year never
4
15
11
0
0

Q17: Do you have suggestions on how to improve the VLBI school? If so, please indicate
how?
• Keep doing it in Canary Islands.
• I would suggest shortening some talks to 45 min or less.
• Whether to share the course ppt with everyone before training.
• Holding time can be extended, preferably 4-5 days.
• The days were too long. I would have preferred one more day and more exercises.
• More days to have so much information or special time for the most up-to-date one.
• End-to-end scheduling, correlation and analysis of the same session throughout all thepractical sessions.
• Again, the number of hands-on server accounts. It would be nice if there are more, e.g 2
or less students per account.
• I think 3 days are not sufficient time to learn that amount of information. Maybe 4 or 5days school is better.
• No.
• In general, I think it is really well organized.
• Maybe one extra day.
• More time to explain more stuff in detail (derivations of formulas etc.)• Change some lecturers, distribute software better, more hands on exercises using state of
the art software (no calculations by hand).
Appendix-B Page-11

• In some ”cases” of lecture exercises, it would be better if we follow the lecturer and he/she
explain every necessary step. Specially those related to correlation and data analysis. It
will allow us to ask questions at the same time we make the exercise.
• More fancy presentation tools (e.g., gifs+animations), more interaction with audience(questions + 60 sec tasks), 10-point multiple choice quiz after every lecture (5 min) -¿lecturers get feedback on how well the job was done.
• Shorter days. Make activity groups 3 people or less (hard to get 4 people around a screen).
Perhaps having a mentor or experienced user for each group if possible (ex. Fourfit tutorial). Try to make lecture slides available before the school (easier to follow along/takenotes on things if you have everything right in front of you).
• To give the presentation notes or slides before the school.
• More time for solving the practical tasks and a handout for using the software which isused.
• Better explanation of the basics.
• Distribute the amount of info on e.g. 4 days instead of 3.
• Generally is a very good event with top professionals. Maybe there were many lessons ina short time (2 days and a half) and I would extend lunch time a bit (1.5 hours) for thepeople to chat and relax a bit.
• Look for university lectors, create school lectures on-line• The duration of school could be extended to 4 days, more time for exercises.
• More explanation on fundamentals in antenna theory.
• NA
Q18: What is your educational background?
Geodesy
9
Physics/Astrophysics/Astronomy
7
Communication / Electrical / Space Engineering 4
Mathematics
1
Meteorology
1various6

Q19: If relevant, how many years have you been active in VLBI?
≤ 1 year 1 ≤ 2 years 2 ≤ 5 years > 5 years
10
7
7
4

Q20: Any more feedback from your side?
• Keep doing it, it was awesome and very useful!
Appendix-B Page-12• Thank you very much for the organization!
• NO?Thanks?
• No• Thank your for giving us this kind of opportunity !
• I was satisfied with the school. Thank you!
• The school is VERY helpful! Thanks a lot for organizing!
• Thanks for very interesting lessons!
• Altogether, it was great to get the overview. I was hoping to understand more details, butthat cannot happen in three days, at least not with me. The reason why I would not pay for
another school is simply because I have been there now, and any next time (in a few years)
would be hard to justify. In fact, I think it is worth paying for!
• Please add one extra day and spread out the lectures over 4 days. Or shorten/remove sometalks. You can shorten: What do we use to observe? How do we store and transport data?
and Digital backends (bring less details, focus more on general idea)• It was a very nice experience and very well organized.
• No• Thank you for let me be part of this school• No• Well, I’m starting in VLBI. Maybe you could send an email with some weblinks to ’mustread’ paper, articles, webs, etc. before the school for the students to get familiar with them.
• NA

Appendix-B Page-13

Selected photos from the VLBI school

Fig. 2: The VLBI school banner.

Fig. 3: The lecture hall for the VLBI school.

Appendix-B Page-14

Fig. 4: The lecture hall for the VLBI school.

Fig. 5: Gino Tuccari explaining Nyquist sampling.

Appendix-B Page-15

Fig. 6: Coffee break with intense discussions.

Fig. 7: Real observations during the VLBI school.

Appendix-B Page-16

Fig. 8: Axel Nothnagel helping during the exercises.

Fig. 9: VLBI school lunch.

Appendix-B Page-17

Fig. 10: Members of the LOC for the VLBI school.

Fig. 11: The VLBI school dinner.

Appendix-B Page-18

EVGA 2019 Organization

The National Geographic Institute (IGN) of Spain is a General Directorate depending on the
Ministry of Public Works of Spain (Ministerio de Fomento). It performs, among others, thefunctions of planning, scientific exploitation, technological development and operational management of its own astronomical, space geodesy and geodynamical instrumentation and infrastructures, and the planning and management of national passive and active geodetic networks.
To this end, it has a network of geodetic stations distributed through the country and an Observatory in Yebes (Guadalajara, Spain) with two radio telescopes of 40 meters and 13.2 meters indiameter respectively and laboratories for the development of radio astronomical instrumentation. It is currently deploying a network called RAEGE (“Atlantic Network of Geodynamical
and Space Stations”), in collaboration with the Regional Government of Azores, which willconsist of four geodynamical stations in Yebes (Guadalajara, Spain), Artenara (Gran Canaria,
Spain), Santa Maria and Flores (Azores, Portugal).

The National Center of Geographic Information (CNIG) is an autonomous entity assigned
to the National Geographic Institute (IGN) that aims to produce, develop and distribute theworks and publications of geographical nature that the society demands, including the commercialization of those performed by the IGN in execution of the functions that are legally
attributed to it, the elaboration of derived and thematic products and their national and international distribution, without prejudice to the possible competences conferred to other entitiesof the Administration in the production and maintenance of various cartographic products,
with special dedication to the realization of projects based on advanced technologies, researchand development programs and provision of technical assistance in the field of geographic
sciences and techniques.
Appendix-C Page-1

The ULPGC, established in 1989, has more than 25,000 students and 1,500 lecturers. It hasmodern facilities and equipment, with Wi-Fi area in all its centres.
The ULPGC offers the university community a wide range of cultural and sports activities
to complement academic learning, promoting values such as solidarity, social justice, genderequality, and respect for diversity and the environment among members of the community.
The ULPGC is a leading university in e-learning. Degrees and Master programmes as well
as a wide range of courses at all learning levels are offered online. The ULPGC has signed
agreements with universities from the five continents, to facilitate the mobility of teachers,
researchers, students, and administrative staff.
In 2007, the ULPGC won the Quality Award for Public Service and Special Mention forBest Management Practices, both from the Government of the Canary Islands. In 2010, the
ULPGC was evaluated by an International Committee and earned the qualification of Campus
of International Excellence, from the Ministry of Education of the Government of Spain.
It also develops an intense work in the field of development cooperation. It is worth noting theachievement of several UNESCO Chairs at the ULPGC.

Appendix-C Page-2

EVGA 2019 Sponsors

The local government of Gran Canaria Island is ruled by
the Cabildo. This institution with more than 100 years ofhistory is in charge of many infrastructures, nature protected areas, tourism, culture, etc. The Cabildo of Gran
Canaria is not only supporting the EVGA meeting but
also the deployment of the future radio telescope for
VLBI purposes on the island.

Established as a non-profit making Foundation, it is born
thanks to the joint efforts of local public institutions
and private companies of the tourist sector. It is actually composed of the following members: Tourist Boardof Gran Canaria, The Town Hall of Las Palmas de Gran
Canaria, Foundation Las Palmas de Gran Canaria Auditorium, The Canarian Institution of Trade Fairs, Expomeloneras, The Hotel, Restaurant and Cafe Business
Employers Federation of Las Palmas and Chamber ofCommerce, Industry and Navigation Services Gran Canaria.
MT Mechatronics GmbH, located in Mainz, Germany,
provides global services as prime contractor for design, development, system integration, commissioning,training, maintenance and operations for communicationand deep space antennas, radio and optical telescopes,
mechatronic equipment for research institutions, launching facilities for the European space program and large
medical systems for the next generation of particle cancer therapies. With over fifty years of experience in thetelescope and antenna business MT Mechatronics has
assembled a highly qualified team of engineers and experts with all relevant capabilities and experience to provide the best value and highest quality for your Mechatronic product.
Appendix-C Page-3

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GOBIERNODE ESPAÑAMINISTERIODE FOMENTO

INSTITUTOGEOGRÁFICONACIONAL

Centro Nacional de Información Geográfica
Instituto Geográfico Nacional (Ministerio de Fomento)
Calle General Ibáñez de Ibero, 328003 Madrid
www.ign.es - consulta@cnig.es