ISSN 1882-3440

NATIONAL INSTITUTE OF INFORMATION AND
COMMUNICATIONS RESEARCH LABORATORYCOMMUNICATIONS TECHNOLOGY

Serial No. 29

October 2008

CONTENTS
The 7th NICT IVS-TDC Symposium
Hiroshi Takiguchi and Yasuhiro Koyama...... 1

Proceedings of the 7th NICT IVS TDC Symposium (Kashima, February 15, 2008)
A Comparison between Current Mapping Functions and Ray-traced Slant . . . . . . 3
Delays from JMA Mesoscale Numerical Weather Data
Ryuichi Ichikawa, Thomas Hobiger, Yasuhiro Koyama, and Tetsuro Kondo
Integer least-squares adjustment for VLBI
Thomas Hobiger, Mamoru Sekido, Yasuhiro Koyama, and Tetsuro Kondo...... 8

Development of the software correlator for the VERA system III
Moritaka Kimura. . . . . 12

Developments of K5/VSI System for Geodetic VLBI Observations
Yasuhiro Koyama, Tetsuro Kondo, Mamoru Sekido, and Moritaka Kimura. . . . . 15

Current Status of Development of a Compact VLBI System for Providing . . . . . 19
over 10-km Baseline Calibration
Atsutoshi Ishii, Ryuichi Ichikawa, Hiroshi Takiguchi, Hiromitsu Kuboki, Tetsuro
Kondo, Yasuhiro Koyama, Morito Machida, and Shinobu Kurihara
Comparison Study of VLBI and GPS Carrier Phase Frequency Transfer using . . . . . 23
IVS and IGS data
Hiroshi Takiguchi, Yasuhiro Koyama, Ryuichi Ichikawa, Tadahiro Gotoh, Atsutoshi Ishii, Thomas Hobiger, and Mizuhiko Hosokawa
Development of e-VLBI Technologies for Ultra-rapid UT1 Measurement
Mamoru Sekido, Tetsuro Kondo, Jan Wagner, Thomas Hobiger, Kensuke Kokado,
Hiroshi Takiguchi, Yasuhiro Koyama, Rüdiger Hass, Jouko Ritakari, and Shinobu
Kurihara. . . . . 28

Real-time ray-tracing through numerical weather models for space geodesy
Thomas Hobiger, Ryuichi Ichikawa, Yasuhiro Koyama, and Tetsuro Kondo. . . . . 31

1

IVS NICT-TDC News No.29

The 7th NICT IVS-TDC Symposium
Hiroshi Takiguchi1 (htaki@nict.go.jp) and Yasuhiro Koyama2
1

Space-Time Standards Group, Kashima Space Research Center, National Institute of Information
and Communications Technology, 893-1 Hirai, Kashima, Ibaraki, 314-8501, Japan
2
Space-Time Standards Group, National Institute of Information and Communications Technology,
4-2-1 Nukui-Kitamachi, Koganei, Tokyo, 184-8795, JapanThe 7th IVS (International VLBI Service for Geodesy and Astrometry) TDC (Technical Development
Center) symposium held in Kashima Space Research Center (KSRC) of NICT on 15th February 2008.
This symposium is held every year as a place in which the VLBI researcher exchanges the result ofresearch and progress information. This time, 19 oral presentations and 1 poster presentation were madeat 4 sessions (”Data Analysis and Software Development”, ”System Development”, ”Time and Frequency
Transfer”, ”e-VLBI”). Especially, there were 6 presentations from the student of the Yokohama National
University, that were the wonderful presentation summarized as a master thesis. There was 29 person
participation from the main organizations which do the following VLBI researches. Geograhical Survey
Institute, National Astronomical Observatory, National Institute of Polar Research, Yokohama National
University, and NICT.
In each session, the interesting topics were presented. Especially, the Q and A session about thepresentation of the KARAT which is a software to provide precise ray-tracing results of the atmosphericdelay using numerical weather model, the status of development of the very small VLBI system named
MARBLE, the ultra rapid UT1 estimation using high-speed network, and the plan to make VLBI arrayfrom four over 30m aperture antennas of Ibaraki prefecture by using high-speed network was active.
And also the extra explanation of the modified 2.4m antenna was held at the lunch time.
We would like to thank all participants for the contribution to fruitful symposium. Here we have
8 papers in the proceedings. It would be our pleasure if they are useful to many persons. The materials of these presentations are available on the web at http://www2.nict.go.jp/w/w114/stmp/
ivstdc/sympo080215/twmemo7.html (in Japanese).

October 2008

2

3

A Comparison between Current Mapping Functions andRay-traced Slant Delays fromJMA Mesoscale Numerical
Weather Data
Ryuichi Ichikawa1 (richi@nict.go.jp),
Thomas Hobiger1 , Yasuhiro Koyama1,2 ,and Tetsuro Kondo1,3
1Kashima Space Research Center, National
Institute of Information and Communications
Technology, 893-1 Hirai, Kashima, Ibaraki
314-8501, Japan
2
Space-Time Standards Group,Kashima
Institute of Information and Communications
Technology, 4-2-1, Nukui-Kitamachi, Koganei,
Tokyo 184-8795, Japan3
Department of Space Survey and Information
Technology, Ajou University, Republic of Korea
Abstract: We have estimated atmospheric slantdelays using the KAshima RAytracing Tools(KARAT) through the JMA 10 km MANAL data.
The comparisons between KARAT-based slant delays and empirical mapping functions indicate large
biases ranging between 18 and 90 mm for summer season, which are considered to be caused bya significant variability of water vapor. We also
compared PPP processed position solution using
KARAT with that using the latest mapping function for the two week GEONET data sets. The
KARAT solution were almost identical to the solution using GMF with linear gradient model, butsome cases were slightly worse under the extreme
atmospheric condition. Though we need further investigations to evaluate the capability of KARAT
to reduce atmospheric path delays under the various topographic and meteorological regimes, the
KARAT will be the powerful tool to reduce atmospheric path delay with the numerical weathermodel improvement.

IVS NICT-TDC News No.29

Tools (KARAT)”[4]. First, we compared empiricalmapping functions, developed space geodesy, with
KARAT slant delays. Next, we carried out a preliminary comparison between position repeatabilities of precise point positioning (PPP) estimatesusing KARAT and those using the latest mapping
function.
2.

KARAT

KARAT have been developed at the National Institute of Information and Communications Technology (NICT), Japan and is capable of calculating
total slant delays and ray-bending angles. We perform a successive 19 months run of KARAT calculations from March 2006 to September 2007. The
JMA 10km MANAL data which we used in ourstudy provides temperature, humidity, and pressure values at the surface and at 21 pressure levels(which are equal to steps of several meters to kilometers up to about 31 km), for each node in a 10
km by 10 km grid that covers all Japanese islands,
the surrounding ocean and Eastern Asia[8]. Figure
1 shows the distribution of the total zenith delays
retrieved from the JMA 10-km MANAL data at
1600 UT of July 22nd, 2006.
We first resample the original JMA grid to amodified grid which allows to run the new ray
tracing algorithms using analytic expressions. At
present the 3-hourly operational products are only
available by JMA. Thus, a linear time interpolation is used to obtain results at arbitrary epochs
what allows also to evaluate temporal change of
estimates. The details of KARAT is described inanother paper[4].
3.

Comparison between Mapping Functions and KARAT

We compare empirical mapping functions developed for GPS and VLBI with equivalent slantdelays estimated by KARAT. Modern mapping
functions such as the Isobaric Mapping Function(IMF)[6], Global Mapping Function (GMF)[2], andVienna Mapping Function (VMF)[1] have beensuccessfully used to estimate site dependent zenith
1. Introduction
delays in the past few years. The lateral spatial
variation of wet delay is reduced by linear gradient
We have developed a new tool to obtain atmoestimation. However, the mapping function errors
spheric slant path delays by ray-tracing throughassociated with the lateral heterogeneity of the atthe meso-scale analysis data for numerical weather
mosphere have not been assessed sufficiently so far.
prediction developed by Japan Meteorological
Our aim is to see how well the modern anisotropic
Agency (JMA) with 10 km horizontal resolution[4]mapping functions can mimic the directional vari(hereafter, we call this “JMA 10km MANAL
ability associated with the intense mesoscale disdata”). These data is operationally used forturbances typical of the Japanese monsoon.
the purpose of weather forecast and considered
Figure 2 shows the three typical mapping funcfor our study. We have created ray-tracing routions (NMF, VMF, GMF) for station Kashima (atines and named the tools “KAshima RAytracing
location is shown in Figure 1), Japan from 2005 to4

October 2008

Table 1. Mean bias and standard deviation values of slant delay residuals in millimeter at elevation of
5◦ for 16 IGS stations in the East Asia region.
IGS
VMF-KARAT GMF-KARAT NMF-KARATYSSK-8.3±18.7-10.8±30.6-14.1±32.3
MIZU
16.1±43.6
21.9±50.1
31.3±51.0
TSKB
12.3±48.8
22.6±52.7
38.4±53.4
KSMV
8.9±45.0
19.0±49.6
34.7±50.2
KGNI
20.7±44.927.3±49.7
43.7±50.1
MTKA
17.9±44.1
25.4±48.4
41.9±48.8USUD
56.9±32.1
1.6±35.1
12.1±35.5
BJFS
13.6±37.7
14.6±42.4
24.8±42.9
DAEJ
16.4±64.6
18.9±68.7
36.5±69.7-0.6±54.0
4.0±59.4
20.0±59.3
SUWN
AIRA-78.5±65.4-93.9±63.1-82.1±63.0
GMSD
6.5±50.2
0.5±53.425.2±54.9
CCJM
15.8±65.0
2.5±66.0
28.4±66.7
TWTF
21.5±79.7
5.3±80.042.5±81.4
TCMS
63.5±93.3
53.8±92.9
92.9±94.1
TNML
63.5±93.3
53.9±92.9
93.0±94.1

Mapping Function at 5° Elevation for KSMV

10.3
VMF

GMF

NMF

mapping function at 5°

KSMV
10.2

10.1

10

2006.1

2007.1

2008.1Year

Figure 2. Mapping functions VMF (red, thinsolid), GMF (blue, dash-dot), and NMF (green,solid) for 5◦ elevation at Kashima, Japan (IGS station: KSMV), from 2005 to the middle of 2008.

Figure 1. Zenith total delay retrieved by the JMA
10km MANAL data at the 1600UT of July 22,
2006.

the middle of 2008. The Niell Mapping Function(NMF) (Niell, 1996) is still widely used by manygeodesists. Because it depends only on the station
latitude, height and the day of the year, users caneasily apply it within data processing without insitu meteorological measurements. However, NMF
has significant scale biases reaching values up to

0.015 at an elevation of 5◦ in winter-spring season
in eastern Asia region as compared to VMF and
GMF, shown in Figure 2. Such biases can lead tosignificant station height errors.
On the other hand, both GMF and VMF areconsidered to be globally available to reduce atmospheric path delays for GNSS and VLBI processing. In order to assess the availability of these
mapping functions in the East Asia region, we compared KARAT-based slant delays at elevation of
5◦ from the end of June to September, 2007 witheach mapping function values at 16 IGS stations.

5

IVS NICT-TDC News No.29

We examined both the mean and standard deviation of slant delay residuals. The mean value represents a bias associated with each mapping function, whereas the standard deviation value represents the scatter due to horizontal variability of
atmosphere (mainly caused by water vapor variation). The results are summarized in Table 1 andone example histogram of the residuals at Kashima
is shown in Figure 3.

Number50
40

8.9 +/− 45.0 mm

KSMV

30
20
10
0

Number50
40

19.0 +/− 49.6 mm

30
20
10
0

Number50
40

34.7 +/− 50.2 mm

30
20
10
0
-0.5

-0.4

-0.3

-0.2

-0.1

0
0.1
Difference(m)

0.2

0.3

0.4

0.5

Figure 3. Histogram of residuals in slant delays atelevation of 5◦ from the end of June to September, 2007. Values between VMF and KARAT (upper), those between GMF and KARAT (middle),
and those between NMF and KARAT (lower) are
shown, respectively.
Numerical weather model data are based on thephysical/dynamical equations that govern the atmospheric flow. The JMA 10 km MANAL data are
obtained by combining short model forecasts withnew observations (a process called data assimilation). Therefore, the ZTD obtained from KARAT
can be considered to be the most realistic empiricalvalue of the real atmosphere.
Large biases of more than 10 mm occur at almost stations, even if VMF is applied. In addition,
the scatter of the residuals for all mapping functions is extremely large ranging from 18 to 90 mm,
which is caused by significant variability of water
vapor. Though these results suggest that the latest
mapping functions are insufficient to remove atmospheric path delay in the East Asia region, we needfurther investigations to understand the behaviorof the atmospheric parameters under the various
topographic and meteorological regimes.

4.

Precise Point Positioning Results for
GEONET Stations

In order to compare KARAT processing and empirical mapping functions we analyzed whole data
sets of GEONET (GPS Earth Observation Network System), which is a nationwide GPS network operated by Geographical Survey Institute(GSI). In our comparison about 1360 stations of
GEONET data during July 9th - 23rd of 2007 were
processed.
At first, precise point positioning (PPP) estimates covering the whole period shown above
were obtained for all sites using GPSTOOLS[9].
The troposphere delays have been modeled by dry(using the Saastamoinen model[7]) and wet constituents, whereas the latter one were estimatedas unknown parameters using the GMF together
with linear gradients. The daily position estimatesfrom this solution acts a reference to which the raytraced solutions can be compared (see Hobiger etal., [2008a] in detail.[3]). In our comparison, PPP
estimations using the GMF without linear gradientwere also performed.
Changes in the mapping functions primarily
cause changes of the station heights in general. According to Hobiger et al.[3], the KARAT solutions
are better than the solutions using GMF with gradient during a period of 4 months. In our comparison, the averaged vertical repeatabilities of all
solutions demonstrate a similar nation-wide pattern as shown in Figure 4. The largest repetabilities more than 10 mm, which occur in Kyushu andShikoku islands which are located in the west ofJapan, are reflected in all three figures. In addition, Figure 5, which shows the repetabilities foreach coordinate component (i.e. the north, east,and vertical errors) for all three solutions, indicatesthat the KARAT solution is slightly worse than the
GMF with gradient solution. On the other hand,
KARAT solution is better than the GMF without
gradient solution for horizontal component.
During the whole processed period both Kyushu
and Shikoku islands have undergone severe heavy
rain fall event due to the Baiu front and the tyhoon “MAN-YI” passing and cumulating in precipitation amounts ranging 500 - 1100 mm. The
time-resolution of the JMA 10km MANAL data isthree hours, whereas the PPP processing including
gradient estimation was performed for 300 seconds
interval. Under the extreme atmospheric condition
such as the concerned period, out results imply thatthe performance of KARAT is almost equal to thesolution using the GMF with gradient. We needto extend the processing period for our comparison in order to evaluate a KARAT capability in a
reduction of atmospheric path delay.

6

October 2008

500
KARAT

GMF + gradient

GMF

repetability of north position
400

KARAT: 3.4 ± 4.1mm

NUMBER OF CASES

GMF with gradient: 2.7 ± 3.5mm
GMF w/o gradient: 4.4 ± 4.9mm

300

200

100

0
0

10

20

KARAT

GMF + gradient

30

500
GMF

repetability of east position
400

KARAT: 5.3 ± 6.5mm

NUMBER OF CASES

GMF with gradient: 5.0 ± 6.2mm
GMF w/o gradient: 5.5 ± 6.6mm

300

200

100

0
0
500

10

20

KARAT

GMF + gradient30
GMF

repetability of vertical position
400

KARAT: 7.5 ± 8.0mm

NUMBER OF CASES

GMF with gradient: 6.9 ± 7.4mm
GMF w/o gradient: 7.5 ± 7.9mm

300

200

100

0
0

10
20
repetability in millimeter

30

Figure 5. Histogram of repeatabilities for each coordinate component (north, east, and vertical) for
each solution.

Figure 4. Averaged repetabilities of station heightcomponents between July 9th - 23rd of 2007 for all
GEONET stations. The upper represents the solution using KARAT, the middle represents the solution using GMF with gradient, and the lower represents the solution using GMF without gradient.

The advantage of KARAT is an efficient reduction of atmospheric path delay with the numerical
weather model improvement (i.e. time and spatial resolution, including new observation data). In
spite of the present model imperfectness and coarse
time resolution, we hope KARAT will liberate station position determination from numerical instability of unknown parameters.

7

IVS NICT-TDC News No.29

5.

Summary and Outlook

We have estimated atmospheric slant delays using the KAshima RAytracing Tools (KARAT)
through the JMA 10 km MANAL data. The comparisons between KARAT-based slant delays andempirical mapping functions from the end of Juneto September of 2007 indicate large biases ranging
between 18 and 90 mm, which are considered tobe caused by a significant variability of water vapor. Next, we compared PPP processed position
solution using KARAT with that using the latest
mapping function for the two week GEONET data
sets. The KARAT solution were almost identicalto the solution using GMF with linear gradientmodel, but some cases were slightly worse underthe extreme atmospheric condition. Though weneed further investigations to evaluate the capability of KARAT to reduce atmospheric path delays
under the various topographic and meteorologicalregimes, the KARAT will be the powerful tool toreduce atmospheric path delay with the numerical
weather model improvement.
Acknowledgments: We would like to thank the Geographical Survey Institute, Japan for providing
GEONET data sets. We also thank the Japan Meteorological Agency for providing data and products.
References[1] Boehm, J. and H. Schuh, Vienna Mapping
Functions in VLBI analyses, Geophys. Res.
Lett., 31, L01603, doi:10.1029/2003GL018984,
2004.
[2] Boehm, J., B. Werl and H. Schuh, 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,
2006.
[3] Hobiger, T., Ichikawa R., Takasu T., KoyamaY., and Kondo T., Ray-traced troposphereslant delays for precise point positioning,
Earth Planets Space, 60, e1–e4, 2008a.
[4] Hobiger, T., R. Ichikawa, Y. Koyama and T.
Kondo, Fast and accurate ray-tracing algorithms for real-time space geodetic applications using numerical weather models, J. Geophys. Res., under review, 2008b.
[5] Niell, A. E., Global mapping functions forthe atmosphere delay at radio wavelengths. J.
Geophys. Res., 101, 3227-3246, 1996

[6] Niell, A. E., A. J. Coster, F. S. Solheim, V.
B. Mendes, P. C. Toor, R. B. Langley, and C.
A. Upham, Comparison of measurements ofatmospheric wet delay by radionsonde, water
vapor radiometer, GPS, and VLBI, J. Atmos.
Oceanic Technol., 18, 830-850, 2001.
[7] Saastamoinen, J., Contributions to the theory of atmospheric refraction, part 2, Bull.
Géodésique, 107, 13-34, 1972.
[8] Saito, K., et al., The Operational JMA Nonhydrostatic Mesoscale Model, Monthly Weather
Review, 134, 1266-1298, 2006.
[9] Takasu, T. and S. Kasai, Evaluation of GPS
Precise Point Positioning (PPP) Accuracy,
IEIC Technical Report, 105(208), 40-45, 2005.

8

October 2008

Integer least-squares
ment for VLBI

adjust-Thomas Hobiger (hobiger@nict.go.jp),
Mamoru Sekido, Yasuhiro Koyama,
and Tetsuro Kondo
Kashima Space Research Center, National
Institute of Information and Communications
Technology, 893-1 Hirai, Kashima, Ibaraki
314-8501, Japan
Abstract: Teunissen (1996) presented an algorithm
which considers the integer nature of unknown parameters within least-squares adjustment. Thismethod has been successfully applied within GNSS
analysis where it helps to solve phase ambiguities.
For this study the algorithm has been adopted to
the needs of VLBI data processing and applied
to simulated and real VLBI data. In particular,
it is shown how this algorithm improves the estimation of ambiguities for next-generation VLBI(VLBI2010) and it is discussed how it can be used
for the automated phase delay connection of fringe
phase data.
1.

Introduction

VLBI observables are, similar as GPS measurements, biased by an unknown but quantized
number of ambiguities which have to be resolved
within post-processing steps. Since sophistcatedand straight-forward algorithms are existing for
ambiguity resolution of GPS phase observations,
we have tried to apply these methods to VLBI.
By two examples we show how integer estimation methods can be applied to next-generation
VLBI (VLBI2010) data using simulated observations which were generated according to the design
specifications of upcoming systems. Additionally
we reveal that the same method can be successfully
applied to the connection of fringe-phases between
consecutive scans.
2.

Integer ambiguity estimation in leastsquares adjustments

Teunissen (1995[10],1996[8]) presented an algorithm, called Least-squares AMBiguity Decorrelation Adjustment (LAMBDA), which allows theminimization of the a objective function
min ||y − Bb − Aa||2Qy −1

where b ∈ Rn and a ∈ Zm

(1)

and also incorporates variance-covariance information of the observations y. The solution of thisproblem is obtained in three steps: a least squaresadjustment, ignoring the presence of integer unknowns; the integer ambiguities a are estimatedusing the variance-covariance information from the”float” adjustment; and the ”fixed solution”, whichis the final solution, is computed assuming that the
integer values have been resolved correctly.
3.

Example 1: Integer ambiguity estimation for VLBI2010-like data

For the purpose of this discussion, VLBI measurements provide two primary types of observation types, those being delays and phases. The
former are not affected by ambiguities while thelatter are. For any given source, the measured de∗lay τi,j(tk ) on baseline i, frequency fj and epochtk can be written as∗τi,j(tk ) =τi (tk ) +Ei (tk ) ∂τi (tk )
+
∆αj
fj2
∂α

∂τi (tk )ε∆δj + τi,j(tk ).
+∂δ(2)

where the non-dispersive delay is denoted by τi (tk ),the ionosphere contribution (proportional to theslant total electron content) by Ei (tk ), the ranε
dom noise of the receiving system by τi,j(tk ), andthe ”core-shifts” (e.g. Fey and Charlot (1997)[2],
Petrachenko and Berube (2007)[6]) by the thirdand fourth terms. Although instrumental delays
may be of concern, they are beyond the scope of
this analysis. It is anticipated that their effectcan be adequately reduced through direct and selfcalibration processes. Phase measurements, in cycle units, can be written in a similar way by
Ei (tk )∂τi (tk )
+ fj
∆αj
fj
∂α
∂τi (tk )+ fj∆δj + Ni,j (tk ) + φεi,j (tk )∂δ(3)

φ∗i,j (tk ) =fj τi (tk ) −where the ambiguity term, denoted by Ni,j (tk ), hasbeen introduced. Although it is possible to estimate all the unknowns using a standard GaussMarkov type least-squares adjustment (e.g. Koch
(1997)[4]), it is more straightforward to incorporate
the added information that the ambiguity values
are integer numbers. In the VLBI case, the algorithm will solve for τi (tk ), Ei (tk ) , ∆αj and ∆δj as
float unknowns and the ambiguities Ni,j (tk ) are obtained as integer parameters. For the simulations
described in later in this section the MLAMBDA
implementation of the algorithm (Chang (2005)[1])
has been used. This algorithm works is a similar
way to the original LAMBDA method but is superior with respect to computation speed.

9The most rigorous approach to resolving the unknown phase cycles (ambiguities) would incorporate all scans that observe the same source intoa single least-squares adjustment, as described in
section 2.. But this strategy is not feasible for two
reasons. Firstly, since the ambiguity search space(Teunissen et al. (1996)[8]) grows with each unknown, and the number of ambiguity terms canbe large, it becomes nearly impossible to resolve
all ambiguities in a reasonable computation time.
Secondly, the core-shift terms (∆αj and ∆δj ) arehighly correlated (> 0.95) with the delay and ionosphere terms, causing the inversion of the variancecovariance matrix to fail or contain elements withunrealistic values, which in turn distorts the integer search algorithm such that the search domain isextended to an incorrect region. In the absence ofthe core-shift terms, this problem would not exist
since each group of frequency related observations
become independent and can be treated separately.
However, in order to take advantage of the integer
ambiguity adjustment methods and to simultaneously estimate the core shifts, a sequential iterativealgorithm (Hobiger et al.(2008)[3]) is used.
In order to verify the algorithms discussed in
the prior section, artificial (simulated) observations
have been created. In general, each scan was assumed to consist of measurements from four different bands (with center frequencies set to 2.5,5.25,
7.0 and 11.25 GHz and a 1 GHz bandwidth per subband) what leads to eight observables (four delays
and four phases) per scan. In total 233 scans, observing a common source, were taken and the artificial observations were created assuming a signalto-noise-ratio (SN R) of 14 for all scans, at first.
ε(tk ) and φεi,j (tk ) were
The noise contributions τi,jobtained from a Gaussian random generator withzero mean and variances of

IVS NICT-TDC News No.29

Figure 1. Absolute mean differences (for SN R 14,
after 100 iterations, red crosses) between the simulated and the recovered delays in dependence ofthe number of observations included in the estimation algorithm. The green boxes denote the maximum absolute error in dependence of the numberof included scans. The blue dashed line reflects one
mm-error level.

span between these observations is small. But assoon as other baselines or further epochs are introduced theses correlations will get smaller and finally dissolve. As shown by Hobiger et al.(2008)[3]
the correct integer value is found after one or two iterations and further iterations don’t lead to the introduction of wrong ambiguities. A slightly larger
number of iterations, which is needed in some of
the cases, is caused by exceptional large random
components. As soon as more observations are included the effect diminishes and the algorithm performs well. In order to verify that the delays arerecovered correctly, the absolute mean differences
between the modeled and estimated values after
100 iterations are plotted for a different numbersof baselines in figure 1.
It can be seen that the average delay estima12N B
NB
2
tion
error is far below the mm-level and that evenστ2 = 2
and
σ
=
(4)
φ
4π SN R2 BW 2
4π 2 SN R2
the absolute maximum error does not exceed thiswhere BW reflects the bandwidth, N B stands for boundary. The plot would look nearly similar when
the number of frequency bands (i.e. 4) and SN R the errors are computed directly after the integer
denotes the overall signal-to-noise ratio, which cor- ambiguities have been fixed, but the maximum erresponds to the multi-band delay error. The num- rors would be slightly bigger. The reason for thisber of iterations was set to 100 in order to check is that it takes some iterations more to separate
the performance and behavior of the integer am- delays, ionospheric effects and source structure efbiguity resolution strategy. Moreover the number fects completely. In order to demonstrate that theof included observations has been varied between integer estimation strategy is superior to conven4, which is the minimum number of observations tional least-squares techniques, such a solution hasthat provide an overdetermined system, and the been computed too. But since it is not possible
maximum number of scans (i.e. 233). Since the al- to estimate all parameters in one huge adjustment
gorithm is not depending on the observation geom- a similar iterative strategy as for the integer estietry, the introduction of a new baseline is expected mation has been applied. The only difference was
not to distort the estimation process. From a math- that instead of the MLAMBDA algorithm a simple
ematical point of view there might be a correlation nearest-integer operator computes the integer ambetween scans from a single baseline when the time- biguities from the float solution in each iteration.

10

October 2008

Figure 2. Results from the integer rounding approach (see text). The meaning of the symbols is
identical to fig. 3.
Figure 2 shows how the recovered delays are differing from the original values after 100 iterations,when the integer rounding strategy is applied.
It is clearly visible that the delays can not be recovered with the same accuracy, even after 100 iterations. Although the absolute mean error is below
the one-mm level for a few baseline combinations,the error is on average at the order of 20 ps (7 mm)
and the absolute maximum error is around 100 ps(about 3 cm). The reason for the bad performanceof the rounding algorithm is due to the fact thateven after 100 iterations, the rounding algorithm
does not resolve the integer ambiguities correctly(not shown here).
In order to check the behavior of the algorithm fordifferent SN R levels, 730 Monte-Carlo simulated
runs (i.e. equal to 2 years of continuous observation) were carried out. Figure 3 shows the averaged ambiguity resolution performance together
with the corresponding delay recovery errors.
It can be seen that if the number of scans is larger
than 150 all phase cycles can be resolved, down to
SN Rmin = 12. If 100 scans are taken only, lessthan 1% of the ambiguities can not be resolved on
average for SN R ≥ 13. For the cases using 25 and
50 scans it becomes difficult to resolve ambiguities
since in some of the runs the core-shifts can not
be decorrelated from the other parameters. Thusin the case that the ambiguities are resolved, themean recovered errors follows exactly the theoretical curves. The equivalent single scan error canbe approximated by multiplying the delay recov√
ery errors by nrscan . For 150 and 233 scans it
can be verified that the delays per scan can be reconstructed with an error of less than 1.5 ps (0.5mm) when the SN R is higher than 11. Thus, inorder to apply the algorithm in future VLBI processing it is recommended to observe each source
more than about 150 times at SN R ≥ 12 in orderFigure 4. Fringe-phases (in cycles) before (blue)
and after (green) connection by fitting Cubic-Spline
functions (red) together with integer amgiguities.
Horizontal axis shows time in seconds.
to reliably resolve all the phase ambiguities. Although the algorithm will work in many cases witha a lower number of scans, mathematical correlations between the unknowns can prevent a successful recovery in some of the experiments.
4.

Example 2: Connection of fringe phases
between consecutive scans

In order to increase the performance of ∆VLBI
observations it is necessary to realiably connect thephase delays (i.e. fringe phases) between consective
scans. In our recent studies (Kondo et al.(2008)[5])
we have focused on the maximum scan gap limit
which permits fringe phase connection. Based onthese findings we have tried to apply Teunissen’salgorithm, for ∆VLBI. Since the unknown phase
cycles are quantized in units of 2π the integer ambiguity algorithm can be used for this problem,
too. One has to model the overall phase-delay
behaviour by a continous function (e.g. a cubicSpline function) and estimate the parameters of
this function together with the integer ambiguities, which determine the unknown phase cyclesof each sub-scan. Figure 4 shows how the algorithm performs for a single-baseline ∆ VLBI experiment, tracking a satellite. Ongoing investigations
include multi-baseline experiments which allow us
to inlcude phase-closure conditions within the adjustment process.
5.

Discussion

It was shown that integer ambiguity estimation
is not only useful for GPS, but can also be applied
to VLBI. Since the method is based on stochastics
it provides the most-likely integer values and thus is

11

IVS NICT-TDC News No.29

Figure 3. Performance of the integer ambiguity algorithm obtained as mean values from 730 simulatedruns, each iterated until the change of the squared sum of improvements of the core-shift positions wasless than one µasec2 . The left figure shows the ratio of unresolved ambiguities in dependency of the
SN R level, tested for a different number of observations. The right figure shows the corresponding delay
reconstruction error. Additionally the theoretical formal errors for 150 and 233 observations are plotted
as reference, whereas it was assumed that phase delays can be referred to a mean frequency of 6.5 GHz.
superior to other algorithms based on rounding orother fuzzy criteria. Moreover the algorithm can beapplied to classical least-squares adjustment after
small modifications of the algorithms and allows to
obtain formal errors of all unknowns, including the
integer values.
Acknowledgments: We are very grateful to Prof.
Chang from McGill University, Canada for providing the MLAMBDA code. The first author wants
to thank the Japanese Society for the Promotionof Science (project P06603) for supporting his research. We are thankful to Bill Petrachenko for imparting knowledge from his studies. Patrick Charlot and Arthur Niell are acknowledged for providing
schedules and source structure parameters.
References[4] Koch, K.R. (1997), Parameter Estimation andHypothesis Testing in Linear Models, Springer,
Berlin.
[5] Kondo T., T. Hobiger, M. Sekido, R. Ichikawa,
Y. Koyama and H. Takaba (2008), Scan gap
limits on phase delay connections in VLBI observations, submitted to Earth, Planets andSpace.
[6] Petrachenko B. and M. Berube (2007),VLBI2010 Source Map Alignment Simulation,
IVS Memorandum, 2007-008v01, International
VLBI Service for Geodesy and Astrometry.
[7] Teunissen, P.J.G. (1995), The least-squares ambiguity decorrelation adjustment: a method
for fast GPS integer ambiguity estimation, Journal of Geodesy, 70 (1-2), 65–82,
doi:10.1007/BF00863419.

[1] Chang, X.W., X. Yang, and T. Zhou (2005),
MLAMBDA: a modified LAMBDA method [8] Teunissen, P.J.G., P.J. de Jonge and C.C.J.M.
for integer least-squares estimation, Journal ofTiberius (1996), The volume of the GPS amGeodesy, 79 (9), 552–565, doi:10.1007/s00190biguity ambiguity search space and its rele005-0004-x.
vance for integer ambiguity resolution, Proc.
ION GPS ’96, 17-20 September 1996, 889–898.
[2] Fey, A.L. and P. Charlot (1997), VLBA Observations of radio reference frame sources. II. Astrometric suitability based on observed structure, Astrophys. J. Suppl., 111 (95).
[3] Hobiger T., M. Sekido, Y. Koyama and T.
Kondo (2008), Integer ambiguity estimation in
next-generation geodetic Very Long Baseline
Interferometry, Advances in Space Research,
accepted, 2008

12

October 2008

Development of the software
correlator for the VERA system III
Moritaka Kimura (mkimura@nict.go.jp)
Kashima Space Research Center,
National Institute of Information andCommunications Technology, 893-1 Hirai,
Kashima, Ibaraki 314-8501, Japan
1.

Introduction

The National Institute of Information and Communications Technology (NICT) and the National
Astronomical Observatory of Japan (NAOJ) havedeveloped new software correlation system for the
VLBI Exploration of Radio Astrometry (VERA)
project. Completely same functions as the hardware correlator used in the VERA Project has been
attained in the software correlation system. The
data rates supplied from each radio telescopes are
1024Mbps. This software correlator has attained
the same processing speed as the hardware correlator of the VERA system by only five sets of PC
and disk arrays. Some benchmark tests, comparison of the results with the hardware correlator aredescribed in the past TDC news [2]. Some information of the software correlation systems whichwere not described before introduce this time.
2.

Design of the software correlator

The basic design of the VERA software correlator is the same as the K5/VSI correlator named
GICO3 developed by NICT [1]. The GICO3 is acorrelator of the FX type that processes multi baselines at the same time. Internal block diagrams ofthe correlation process in the GICO3 is shown in
the figure 1 in a simple case of two stations named’A’ and ’B’. In order to achieve high performance,
the GICO3 have double buffer at each stations forparallel processing. One buffer is used for file access

Buffer [0][A]
Raw-File [A]Buffer [1][A]

Raw-Float
Conversion

and another buffer is used for numerical operation.
There are one file access thread and some numerical operation threads generated at the same time.
Since components of the K5/VSI were chosen sothat file access time and numerical operation time
may become equal, compared with sequential processing of numerical operations after file access are
performed, correlation processing is completed inhalf time by parallel processing. VLBI observation
data named ’raw-file’ are converted into the floating point data by using the table lookup algorithm,
because floating point operations are necessary to
express the internal expression in the correlation
process of the FX type correlator. For correlation
process of the multi channel observation, a single
channel is picked and converted into floating point
data at here. Since, the delay tracking and thephase tracking are perform in the frequency space,real-FFT algorithm can be used. As a result, computing time in the FFT becomes half comparedwith complex-FFT algorithm. The delay tracking
and the phase tracking in the frequency space are
performed by correcting phase gradient and intercept. In order to exclude the operation of trigonometric functions which need very long processor
clocks, the table lookup algorithm of 256 sin-cos
elements is used. Auto-correlation and the crosscorrelation are calculated at once, and the integrated results are recorded in the correlation output files periodically. A lot of numerical processing
are perform by vector operations and some functions are described by assembler language. For thisreason, total speed of the GICO3 has attained thesame speed as a hardware correlator using five setsof PC.

Real-FFT

Delay-Phase
Tracking

Auto-Correlation
Cross-Correlation

Buffer [0][B]
Raw-File [B]Buffer [1][B]

Raw-Float
Conversion

Real-FFT

Delay-Phase
Tracking

Figure 1. Block diagram of the GICO3 correlator in a case of two stations.

Auto-Correlation

13
3.

IVS NICT-TDC News No.29

The Correlation Schedule of the GICO3<clock key="D">-omission-</clock>

The correlation schedule of the GICO3 is described by the XML language. A new item canbe easily added. A simple correlation schedule isdescribed in the following. Specification of some
digital backends and translating rules that convert
raw-file into floating point value are assigned in”terminal” items. Position of the radio telescopes,
the name of a digital backend and a name of thedirectory which stored observation raw-file are assigned in ”station” items. By assigning several different backend name in the ”station” items, correlation with mixed digital backend can be possible.
The Name of radio source whose position is used
for geometric delay calculation, the index which
distinguishes a specific A/D channel in the raw-filewhich have several channels and some information
are assigned in the ”stream” items. Correlation
processing of multi-channel observations and / ormulti-beam observations are possible by assigningseveral streams.

<source name="3C345" ><ra> 16h42m58.80997</ra><dec>+39d48’36.99406</dec></source><source name="NRAO512">-omission-</source><stream><label>CH01</label><source>
3C345</source><frequency>+22220000000</frequency><channel>01</channel><fft-point>2048</fft-point><output-Hz>1</output-Hz></stream><stream><label>CH02</label><source> NRAO512</source><frequency>+22220000000</frequency><channel>02</channel><fft-point>2048</fft-point><output-Hz>1</output-Hz></stream><?xml version="1.0" encoding="UTF-8" ?><schedule><process><start>2003/328 01:34:00</start><length>3960</length><object>Multi</object><stations>ABCD</stations></process><terminal name="VERA-01"><speed>256000000</speed><channel>2</channel><bit>2</bit><level>-1.5,-0.5,+0.5,+1.5</level></terminal><station key="A"><name>MIZNAO20</name><pos-x>-3857241.8226</pos-x><pos-y>+3108784.8097</pos-y><pos-z>+4003900.5431</pos-z><terminal>VERA-01</terminal><raw-dir>/mnt/raid/raw-file</raw-dir></station><station key="B">-omission-</station><station key="C">-omission-</station><station key="D">-omission-</station><clock key="A"><epoch>2003/328 01:34:00</epoch><delay>+0.000000000</delay><rate> +0.000000000</rate><acel> +0.000000000</acel><jerk> +0.000000000</jerk><snap> +0.000000000</snap></clock><clock key="B">-omission-</clock><clock key="C">-omission-</clock><process>-omission-</process><process>-omission-</process></schedule>
4.

Multi-Beam Correlation

Since the general radio telescope observed only
one radio source at once. it is designed so thata correlator may also process one radio source atonce. Since the radio telescope used for the VERA
project can observe two radio sources at once, thehardware correlator of the VERA project can process two radio sources at once. When a general
correlator performs the VERA’s two-beam correlation, it is possible by changing radio source positions and performing correlation processing twice,
but it is very inefficient. Since there is no necessitythat software correlator should perform correlation
with fixed processing speed like hardware correlators, it is enables to perform multi-beam correlation whose calculation load are changed dramatically. The GICO3 can perform correlation process
at once with many radio source, and it is effective
to correlate of the masar spots that spread in the

14

October 2008

VERA Correlator

Standard Correlator

GICO3 Correlator  1 1
 

[ , ]







[ (1), (1)]









[ (1), (1)][ (2), (2)] 3

 4

[ (3), (3)][ (4), (4)] 2

[ (2), (2)] 2



Figure 2. left: the standard correlator performs delay tracking to one radio source position. center: the
VERA correlator performs delay tracking to two radio source positions. right: the GICO3 correlator
performs delay tracking to many radio source positions.

celestial sphere widely like a figure 2.
5.

Conclusion

The software correlation system have started
experimental operation in the Mitaka correlator
room. Many kinds of operation tests are also completed and same correlation output results as hardware correlation processing is obtained by software
correlation system. After carrying out durability
test, this system will operate in the part of the
VERA correlation system.
References[1] Kimura, M. , 2-Gbps PC Architecture andGbps data processing in K5/PC-VSI, IVS CRLTDC News, No.23, pp.12-13,November 2003
[2] Kimura, M. , Development of the software correlator for the VERA system II, IVS CRL-TDC
News, No.28, pp.22-25,November 2007

Figure 3. The K5/VSI system installed in the Mitaka correlator room

15

IVS NICT-TDC News No.29

Developments of K5/VSI System for Geodetic VLBI Observations
Yasuhiro Koyama (koyama@nict.go.jp),
Tetsuro Kondo, Mamoru Sekido,
and Moritaka Kimura
Kashima Space Research Center, National
Institute of Information and Communications
Technology, 893-1 Hirai, Kashima, Ibaraki
314-8501, Japan
Abstract: The developments of the K5 VLBI system started in 1999 and diverse component systems have been developed to support various kinds
of VLBI observations and data processing requirements. The main concept of the K5 VLBI system
is to realize real-time VLBI observations and correlation processing performed with various observing modes by combining multiple components ina flexible manner. The system is also intended tobe compliant with the other VLBI related systems
by adopting standardized interfaces. Recently, theK5/VSI Data Recording Terminals and ADS3000+
high speed AD sampler unit have been developed.
The details of these newly developed component
systems will be described.
1.

Introduction

National Institute of Information and Communications Technology (NICT) is one of the technology development centers of the International VLBI
Service for Geodesy and Astrometry (IVS), andwe have been developing VLBI observation systems and data processing systems to improve thecapabilities of the existing systems. In 1999, westarted to develop K5 VLBI system, which consistsof the PC-based data acquisition terminals andsoftware based correlation processing programs. In
contrast to the previous K4 VLBI system developed with the specially designed high speed cassette tape recording system, the K5 VLBI system
is designed with the commodity products such as
personal computers, hard-disks, and network components. This strategy has been quite successful
to develop highly flexible and high performanceobservation systems and data processing systems
for VLBI. As the data acquisition terminals of theK5 system, we have developed two independent series of systems. One is the K5/VSSP system series[Kondo et al., 2003[1]] and the other is the K5/VSI
system series [Koyama et al., 2003[2]]. The concept of the K5/VSSP system and its next generation K5/VSSP32 system is to develop AD sampling

units interfaced to the commodity PC systems byusing the PCI expansion bus (VSSP) and USB2.0
interface (VSSP32). Each AD sampling unit can
support up to four analog inputs, and therefore,
four units are used to record signals from 16 fullchannels of baseband converter units in the caseof usual geodetic VLBI observations. On the other
hand, K5/VSI series are realized by high speed AD
sampler units and all of these units are interfacedwith the commodity Linux PC systems with the
VSI-H (VLBI Standard Interface - Hardware specifications). VSI-H was proposed to define standard
interface for the high speed data transfer between
data input modules, data transfer modules, anddata output modules to improve the compatibility between next generation VLBI observing systems and the correlator systems. To input thedata stream from the VSI-H data input modules, aspecial board called PC-VSI board has been developed. The board is installed to the PCI expansion
bus slot of Linux PC system and can support highspeed data transfer and recording up to 2Gbps witha single unit. Three data sampler units, ADS1000[Nakajima et al., 2001[4]], ADS2000 [Koyama et al.,
2006[3]], and ADS3000 [Takeuchi et al., 2006[5]],have been developed to support various sampling
modes. ADS1000 can sample one baseband channel at the sampling rate of 1024Msps. ADS2000
can sample 16 baseband channels at the sampling
rate of 64Msps suitable for observations using the
bandwidth synthesis method. ADS3000 can sample wide range of baseband frequency band up to
1024MHz with the sampling rate of 2048Msps. A
high speed FPGA (Field Programmable Gate Array) chip is equipped inside the unit and it can beused to process the input data stream for digital filtering and digital baseband conversion processing.
By developing specialized program for the FPGA
chip, ADS3000 has a potential to support various
observing modes without hardware baseband converters.
2.

Developments of the K5/VSI Recording
Terminal

By using the PC-VSI boards which have been expanded to support 2Gbps data rate and commodity raid controller boards, two racks of the K5/VSI
recording terminal have been configured. Figure 1
and Figure 2 are the pictures of the recording terminal taken from the front side and the rear side
respectively. One terminal consists of two rack
mounted Linux operating PC units and necessary
auxiliary components like an LCD display, a keyboard, a mouse, and a switch for these components.
Each unit is installed with a PC-VSI board and araid control board on its PCI expansion bus slots.

16

October 2008

Sixteen 1 TByte hard-disks are controlled by theraid control board to configure RAID-0 system.
Table 1 lists the detailed components used for therecording unit. Each recording terminal is configured with two of these units.

Figure 2. K5 Recording Terminal (Rear View).

Figure 1. K5 Recording Terminal (Front View).

Table 1. Components of the K5 Recording Unit.
CPU (2)
Mother Board
Raid Controller
RAM
HDD (16)

Intel Xeon 2.33GHz
Supermicro X7DBE
Gighpoint RocketRAID 2340
4 GByte (2 GByte x 2)
Seagate ST31000340AS(1TByte SATA 7200RPM)

With one recording terminal, 32TBytes of total data capacity can be used and the data canbe recorded at the data rate of 4.096Gbps by using two VSI-H data input ports. If the data arerecorded continuously, the total capacity can support recordings up to 17.36 hours. The capacity is
considered to be enough for usual VLBI observations where actual recording time is roughly 50The
capacity of the recording terminal can also be enlarged by replacing the hard-disk units if such highvolume hard-disks with more than 1TByte of disk
capacity become available in the future. Since thecommodity raid controller board is used under theLinux PC environment, the data file can be easily
accessed from application programs as simple data
files on the Linux operating system.
It has to be noted that the reliability of therecording terminal is affected by the performance ofthe hard-disk modules. Figure 3 shows the recording performance of the system measured by benchmark program for two different hard-disk modules.
While the module A (Seagate ST31000340AS) cansustain 4Gbps recording speed from the beginningto the end of the total capacity, intermittent performance degradations were recorded with the module
B. Although there are short falls in the recording
speed with the module A, such events can be recovered by the data buffer on the hard-disk modules and data loss did not occur at all during several recording tests. The large recording speed
falls with the module B were larger than the capacity of the data buffer, and actual data losses
occurred. But, even with this configuration, it isworth noted that the recording is maintained withadequate flagging to the data and it is still possible to correlate the data with the other stations’recorded data by suppressing integration to the lost
data segments.

17

IVS NICT-TDC News No.29

Figure 3. Recording speed performance with hard-disk module A (Seagate ST31000340AS) and module B.
3.

Developments of the ADS3000+

After developing two units of the ADS3000 highspeed AD sampler units, we started to extend thecapabilities of the ADS3000 system by adopting
faster AD sampler chip and two new FPGA chips
replacing one FPGA chip. The EV8AQ160 AD
sampler chip was recently released from e2V corporation and it has a capability to sample high speed
analog data up to 5GHz. The chip can work at
the clock rate of up to 2.5GHz and the input signal
can be sampled synchronized to the external clock
signal and additionally at the timing every half ofthe timing of the external clock signal. By using
this capability, the maximum sampling speed of
the ADS3000+ system has become 4096Msps. To
process the high speed digital data from the sampler chip, two FPGA chips are used. Two FPGA
chips are cascaded on the processing board of the
ADS3000+ system. The first stage FPGA chip isused for the processing which require high speed
data handling, such as demultiplexing and multiplexing the data, and the second stage FPGA
chip is used for the complex data processing, suchas digital filtering and digital base-band converter
processings. Table 2 shows the major specificationsof the ADS3000+ system. Figure 4 shows the picture of the ADS3000+ system and Figure 5 shows
the schematic configuration of the main processing
board of the ADS3000+.
Table 2. Specifications of the ADS3000+ unit.
AD chip
Size
Sampling ModesFPGA chip 1
FPGA chip 2

e2V EV8AQ160
EIA 2U (480mm x 88mm x 430mm)
4096Msps x 1ch
2048Msps x 2ch
1024Msps x 4ch (option)
Xilinx Virtex5 XC5VLX110-3
Xilinx Virtex5 XC5VLX220-2

Currently, necessary software programs to beloaded on two FPGA chips are under developments. At beginning, only limited simple function
will be realized and ADS3000+ will support simple
observing modes, such as 2048Msps 2 IF channels
mode and 4096Msps 1 IF channel mode. In thenext step, digital filtering and baseband converting
programs will be loaded on the second stage FPGA
chip to support multiple channel observations. If
this capability is realized, currently used hardware

18

October 2008

Figure 5. Schematic diagram of the ADS3000+ logic board.
References[1] Kondo, T., Y. Koyama, J. Nakajima,
M. Sekido, and H. Osaki, Internet VLBI
system based on the PC-VSSP (IP-VLBI)
board, New Technologies in VLBI, ASP
Conference Series. Vol.306, pp.205-216, 2003.
[2] Koyama, Y., T. Kondo, J. Nakajima,
M. Sekido, and M. Kimura, VLBI observation systems based on the VLBI Standard
Interface Hardware (VSI-H) specifications,
New Technologies in VLBI, ASP Conference
Series, Vol.306, pp.135-144, 2003.

Figure 4.
View from the front side of the
ADS3000+ system.
baseband converter units will become unnecessary
and the VLBI observing system will become much
simpler.
Acknowledgments: Developments of the K5/VSI
system cooperative efforts between NICT, DIGITALLINK Co. Ltd., Japan Communications
Equipment Co. Ltd., COSMO RESEARCH Corp.,
and Elecs Industry Co. Ltd. The authors would
like to express appreciation to the close cooperations of the K5 system development team.

[3] Koyama, Y., T. Kondo, M. Kimura,
M. Hirabaru, and H. Takeuchi, Real-timeHigh Volume Data Transfer and Processing
for e-VLBI, Advances in Geosciences, Vol.6,
Hydrological Science pp.81-90, 2006.
[4] Nakajima, J., Y. Koyama, M. Sekido,
N. Kurihara, T. Kondo, M. Kimura, and
N. Kawaguchi, 1-Gbps VLBI, the First Detection of Fringes, Experimental Astronomy,
Vol.11, pp.57-69, 2001.
[5] Takeuchi, H., M. Kimura, J. Nakajima,
T. Kondo, Y. Koyama, R. Ichikawa, M. Sekido,
and E. Kawai, Development of 4-Gbps Multifunctional VLBI Data Acquisition System,
Publications of the Astronomical Society of the
Pacific, Vol.118, pp.1739-1748, 2006.

19

IVS NICT-TDC News No.29

Current Status of Developmentof a Compact VLBI System for
Providing over 10-km Baseline
Calibration.
Atsutoshi Ishii (ishii@nict.go.jp)1,2,3 ,Ryuichi Ichikawa2 , Hiroshi Takiguchi2 ,Hiromitsu Kuboki2 , Tetsuro Kondo2 ,Yasuhiro Koyama2 , Morito Machida1 ,and Shinobu Kurihara1
1

Geographical Survey Institute
1 Kitasato, Tsukuba, Ibaraki 305-0811, Japan
2
Kashima Space Research Center,
National Institute of Information andCommunications Technology, 893-1 Hirai
Kashima, Ibaraki 314-8501, Japan
3
Advanced Engineering Services Co.,Ltd.
1-6-1 Takezono, Tsukuba, Ibaraki 305-0032,
Japan
Abstract: We are developing a compact VLBI system with 1.65 m diameter aperture antenna in order to provide reference baseline lengths for calibration. The reference baselines are used to validate
surveying instruments such as GPS and EDM andmaintained by the Geographical Survey Institute(GSI). The VLBI system is designed to be assembled with muscle power simply in order to perform
short-term (about one week) measurements at several reference baselines in Japan. We plan to use abroad-band dual-polarized antenna for feed horn of
this VLBI system. Antenna pattern of this broadband feed horn was measured in an anechoic chamber. Using the measured antenna pattern and antenna analysis software, the optimum F/D of mainreflector was estimated. We have also evaluateda front-end system with a broad-band feed hornby installing it on the 2.4 m diameter antenna at
Kashima. On December 5 of 2007, we have successfully detected fringes of the 3C84 signal for
S/X band using 2.4m antenna and 34m antennain Kashima.
1.

Introduction

National Institute of Information and Communications Technology (NICT) are developing a compact VLBI system with 1.65 m diameter aperture antenna in collaboration with GSI. GSI has
a responsibility to calibrate and validate survey
instruments such as GPS receivers and ElectroOptical Distance Meter (EDM). The validation
works are operationally carried out at a 10 km reference baseline maintained by GSI, which is locatedabout 5 km east from GSI headquarters, Tsukuba,

Japan. Along the baseline, pillar monuments madeof stainless steel are installed. To guarantee thequality of validation, the baseline length has to be
examined routinely. However, the entire distanceof the reference baseline too long to be measured
by a EDM directory, the examination at present
are only performed by GPS receiver.
On the other hand, Geodetic VLBI technique
can give an independent measurement to examine
the baseline with a few millimeters accuracy. Thus,
we made idea of the geodetic VLBI system thatcombined a small antenna and a big antenna forthe purpose. This VLBI system is using a pair ofvery small antennas combined with a large aperture antenna (Figure 1). Those small antennas
will be installed at both ends of the reference baseline. However, time delay between small antennas
is directly undetectable due to their low sensitivity.
Two time delays between each small antenna andthe large one can be detected. Time delay between
small antennas can be obtained from those timedelays indirectly. We named the idea ‘Multiple
Antenna Radio-interferometry of Baseline Length
Evaluation (MARBLE)’.
In this article, we describe development of thecompact VLBI system which is the core equipmentof MARBLE.
2.

Development

2.1

Compact VLBI System

The main part of the MARBLE system is thecompact VLBI system as described so far. To perform short-term (about one week) measurements
at several reference baselines in Japan, the mostimportant idea in developing the VLBI system istransportability. The VLBI system consists of a
1.65 m diameter aperture antenna, a front-end
unit, a down converter unit, a azimuth drive unit, aelevation drive unit, and etc (Figure 2). The mainreflector, the azimuth drive unit, and the elevation
drive unit are detachable respectively. These aredesigned to be assembled without heavy machines.
To calibrate ionospheric path delay error, this system can receive the X-band and S-band. A broadband dual-polarized horn antenna (ranging 2 GHz- 18 GHz [2]) made by ETS-Lindgren will be used
as a feed horn of this antenna to achieve it. Thissystem can also equip a target marker for local tie
measurement in the point of intersection of Az-El
drive axes.
2.2
2.2.1

Design and Test The Components
Design The Antenna

The type of antenna of the compact VLBI system was designed to front-fed paraboloid, since the20

October 2008

efficient collection of radio waves with a small aperture and the processing were easy. A paraboloid
reflector can be defined by a F/D where F is a focal length and D is a diameter. The optimum F/Dof the main reflector of compact VLBI system wasestimated as follows method. First of all, the antenna pattern of the feed horn was measured in an
anechoic chamber (Figure 4). Based on the measured antenna pattern, the aperture efficiency offront-fed paraboloid was calculated using antenna
analysis software GRASP8 [3] with several F/Dvalues. Moreover, a noise from the spillover wasconsidered. Consequently, the estimated optimum
F/D was 0.45 to 0.52. Actually, the main reflector
which F/D is 0.45 (D=1650mm, F=740mm) was
produced as a prototype.
2.2.2

Acknowledgments: We would like to thank memberof Nippon Total Science, Inc. and Visual Metrology
Institute, Corp. for their achievement of surface
measurement of the main reflector.
References[1] Ishii, A., R. Ichikawa, H. Kuboki, Y. Koyama,
K. Takashima, and J. Fujisaku, VLBI Experiments Using CARAVAN2400, IVS NICT-TDC
News No.27, pp.9-13, Aug 2006.
[2] Lindgren, ETS-Lindgren (2005). The Model
3164-05 Open Boundary Quadridge Horn, Data
Sheet.
[3] Pontoppidan, K., TICRA, Technical Description of GRASP8, Feb 2003.

Surface Measurement of The Main
Reflector

We measured surface accuracy of the main reflector by using a vision metrology. The vision
metrology system that we used is a very simple
system that used digital camera and note PC. The
measurement accuracy is about 0.1mm on a 2m
object. Figure 3 shows state of this measurement.
Surface accuracy measured was 0.30mm RMS. It
was a good enough compared with the wavelengthof X-band.
2.2.3

Evaluation of Front-end System

We produced a new front-end system with broadband feed horn as a prototype. In order to confirm
its performance, the new front-end system was installed on the 2.4 m diameter antenna at Kashima(CARAVAN2400 [1]). We carried out the fringe
test using CARAVAN2400 and Kashima 34m antenna on December 5 of 2007. We have successfully
detected fringes of the 3C84 signal for both S andX bands on December 5 of 2007 (see Figure 5).
3.

Conclusion

We are developing a compact VLBI system with
1.65 m diameter aperture antenna in order to provide reference baseline lengths for GPS and EDM
calibration maintained by GSI. The antenna of thiscompact VLBI system was designed based on using
the broad-band feed horn. A main reflector was designed with optimum F/D and produced. We also
produced a new front-end system with broad-band
feed horn. In order to confirm this front-end performance, it was installed on the CARAVAN2400.
We successfully detected fringes of the 3C84 signal for both S and X bands using remodeled the
CARAVAN2400.

station R

GPS calibration baseline
station X

station Y

Figure 1. Concept of the length examination for
the reference baseline using VLBI technique.

21

IVS NICT-TDC News No.29

Figure 2. Schematic image of the MARBLE compact VLBI system.

Figure 3. State of surface measurement of the main reflector.

22

October 2008

2.295GHzPort h Hcut

8.436GHzPort v EcutPort v Hcut

20

20

15

15

10

10

5

5
Gain(dBil)Gain(dBil)

Port h Ecut

0
-5
-10

Port h EcutPort h Hcut

-75

-30

Port v EcutPort v Hcut

0
-5
-10

-15

-15

-20

-20

-25

-25
-30

-30
-90

-75

-60

-45

-30

-15
0
15
Angle(deg)

30

45

60

75

90

-90

-60

-45

-15
0
15
Angle(deg)

30

45

60

75

90

Figure 4. Measured antenna patterns of the broad-band feed. Prot v and h are two separate linear
polarizations respectively.

Figure 5. Detected fringes using new front-end.

23

IVS NICT-TDC News No.29

Comparison Study of VLBI and
GPS Carrier Phase Frequency
Transfer using IVS and IGS
data
Hiroshi Takiguchi1 (htaki@nict.go.jp),
Yasuhiro Koyama1 , Ryuichi Ichikawa1 ,Tadahiro Gotoh2 , Atsutoshi Ishii1,3,4 ,Thomas Hobiger1 , and Mizuhiko
Hosokawa5
1

Space-Time Standards Group,
Kashima Space Research Center,
National Institute of Information andCommunications Technology,893-1 Hirai, Kashima, Ibaraki,314-8501, Japan
2
Space-Time Standards Group,
National Institute of Information andCommunications Technology,
4-2-1 Nukui-Kitamachi, Koganei, Tokyo,
184-8795, Japan
3
Geographical Survey Institute,
1 Kitasato, Tsukuba, Ibaraki,305-0811, Japan
4
Advance Engineering Services Co., Ltd
1-6-1 Takezono, Tsukuba, Ibaraki,305-0032, Japan
5
Strategic Planning Department,
National Institute of Information andCommunications Technology,
4-2-1 Nukui-Kitamachi, Koganei, Tokyo,
184-8795, Japan
Abstract: We compare the frequency transfer precision between VLBI and GPS carrier phase using
IVS and IGS observation data in order to confirm
the potential of VLBI time and frequency transfer.
The results show that VLBI time transfer is morestable than GPS time transfer on the same baseline
and same period.
1.

Introduction

Modern cold-atom-based frequency standards
have already archived the uncertainty of 10−15 at a
few days. Moreover cold-atom-based optical clocks
have the potential to realize the uncertainty on a
10−16 to 10−17 level after a few hours (Takamoto
et al., 2005 [6]). On the other hand, time transfer
precision of two-way satellite time and frequency
transfer and GPS carrier phase experiments havereached the 10−10 @1sec (10−15 @1day) level (Rayand Senior, 2005 [5] etc.). In order to compare
such modern standards by these time transfer techniques, it is necessary to average over long periods.

Since these techniques are not sufficient to compare next standards improvements of high precisiontime transfer techniques are strongly desired.
Very Long Baseline Interferometry (VLBI) is oneof the space geodetic techniques measures the arrival time delays between multiple stations utilizing
radio signals from distant celestial radio sources.
By using VLBI, it is possible to measure subtle
variations of Earth orientation parameters (EOP).
In the usual geodetic VLBI analysis, clock offsets
and their rates of change at each station are estimated with respect to a selected reference station.
The averaged formal error (1 σ) of the clock offsets is typically about 20 picoseconds when analyzing geodetic VLBI experiments which are regularly
conducted by the International VLBI Service forGeodesy and Astrometry (IVS). This precision isnearly one order better than other techniques likeGPS or two-way satellite time transfer. It is feasible to use geodetic VLBI for comparison of primary
frequency standards when radio telescopes are deployed at time and frequency laboratories. For thispurpose, we have started to develop a compact andtransportable VLBI system (Ishii et al., 2007 [2]).
To confirm the potential of the current VLBI
time and frequency transfer aiming at the practicaluse in the future, we have compared the results of
the VLBI and GPS carrier phase frequency transfer
using Kashima-Koganei baseline (Takiguchi et al.,2007 [7]). That study showed that VLBI is morestable than GPS between 2000 seconds to 6000 seconds. In this study, we mainly compared VLBI and
GPS carrier phase frequency transfer using datafrom the IVS and the International GNSS Service(IGS) by the same purpose.
2.

The comparison experiments between
VLBI and GPS carrier phase using IVS
and IGS data

We checked the ability of time transfer of VLBI
and GPS carrier phase using IVS and IGS data.
We selected two stations (Onsala, Wettzell) which
belong to IVS and IGS network. These two stations
have in common that at each site VLBI and GPS
are sharing the hydrogen maser (Figure 1). Table
1 shows a list of the data used for this study.
The details of the analysis of VLBI and GPS arelisted as follows:
VLBI• Software : CALC/SOLVE• Strategy– multi baseline– S/X ionosphere-free linear combination– reference station: Wettzell

24

October 2008

Figure 1. Map of IVS and IGS stations in Europe

Figure 2. Time series of the clock offsets after removing linear trend (upper) and the formal error(lower) at Onsala station referred to Wettzell station.

Table 1. Data list
DOY
(2007)
092
100
113
122

Session
R1270
R1271
R1273
R1274

IVS
StationIGS
StationONSALA60,WETTZELL

onsa,
wtzr

the difference between GPS and VLBI clock offsets
showing a good agreement within ±200ps.

• Estimate– station coordinates– atmospheric delay / 1h
– clock offset / 1h
GPS• Software : GIPSY-OASIS II• Strategy– Precise Point Positioning (PPP)(Kouba and Heroux, 2001 [4])• Estimate– station coordinates– atmospheric delay / 5min– clock offset / 5min
• Time Difference– clock offset A − clock offset B
Due to the code noise, the clock offsets of the
GPS solutions show discontinuities at the day
boundaries. The averaged day boundary discontinuity was 94ps. Figure 2 shows one of the VLBI
results of clock offsets. The averaged formal errors (1 σ) of the estimated clock offsets at Onsala
station referred to Wettzell station was 16.1ps.
Figure 3 shows that the time series of the clock
difference between Onsala and Wettzell (session
R1274) calculated from GPS and VLBI respectively (upper part). The lower part of Figure 3 isFigure 3. Time series of the clock difference (upperplot) calculated from GPS and VLBI respectively.
The lower plot is the difference between GPS andVLBI clock offsets. The gap seen on 123(DOY)
was caused by the day-boundary discontinuity ofGPS.
Figure 4 and 5 illustrate the frequency stability of clock difference as obtained from VLBI and
GPS. The short term stability of GPS carrier phaseseems to be slightly better than those from VLBI
for averaging periods up to 103 s. However, VLBI is
more stable at averaging periods longer than 103 s
in any sessions (Figure 5).
In general, the VLBI frequency transfer stability
follows a 1/τ law very close when averaging up to
104 s. And that shows that the stability has reachedabout 2 × 10−11 (20ps) at 1 sec.

25

IVS NICT-TDC News No.29

Figure 5. Modified Allan deviation of VLBI and GPS carrier phase results from all sessions.

3.

Figure 4. Modified Allan deviation (top) and Time
Standard Deviation (bottom) of VLBI and GPS
carrier phase results from R1274 session.

The comparison experiments
KASHIMA-KOGANEI baselineusing

We also carried out geodetic VLBI experiments
using Kashima-Koganei baseline in order to compare the results with GPS time transfer (carrier
phase). We will also use this baseline for test observations of our compact VLBI system which iscurrently under development. The Kashima station which has a 34-m and a 11-m radio telescope,is located about 100 km East of Tokyo Japan. The
Koganei station has a 11-m radio telescope, and islocated in the western part of Tokyo. The baseline
length is 109 km (Figure 6).
Both stations have a permanent GPS receiver(ksmv, kgni and ks34) which are sharing the Hmaser with VLBI since last spring. It was necessary to adopt some parts of these VLBI and GPS
equipment for the needs of the time and frequency
transfer purpose because these systems are usually
set-up for geodetic purposes.
At first, we carried out a test experiment withthe unchanged systems. The details and data quality of the performed VLBI and GPS observations
are listed in Table 2. The quality of the GPS observations was not good (except for the k08049 experiment) due to troubles with the GPS receivers.
In the k08049 experiment we used a new GPS receiver (Trimble NetRS). In this paper, we discuss
only k07166 and k08049 experiments.
The analysis setup is almost the same as the one

26

October 2008

Figure 7. Comparison between VLBI and GPS results (upper plot: clock offsets, lower plot: clockoffsets after removing a linear trend).
Figure 6. Layout map of KASHIMA and KOGANEI station.

Difference (DMTD) method (Komiyama, 1983 [3]).

Table 2. Details of VLBI and GPS observations,which were dedicted to time and frequency transfer.
Data Quality
SessionBaseline

Duration

VLBI
errorserrorsOK
OK

GPS
errorserrorsFailedOK

k07022
K1-Kg
24 hours
k07059K1-Kg
3 daysk07166
Kb-Kg
1 weekk08049Kb-Kg
3 days* K1: KASHIM11, Kg : KOGANEI, Kb : KASHIM34

Figure 8. Layout of the H-maser, GPS receiver and
VLBI antenna.
described in the previous section. The averaged
formal errors (1 σ) of the estimated clock offsets at
Koganei station referred to Kashima station were
23ps (k07166) and 18ps (k08049) in VLBI results.
Figure 7 presents the comparison between VLBI
and GPS. After removing a linear trend (lowerplot), the clock offsets of VLBI reveal a diurnal
variation which can not be seen in the GPS results.
The cable length between the point where the reference signal from the H-maser is injected and the observing system itself is different for VLBI and GPS
as shown in Figure 8. Additionally, the cable of the
VLBI system inside the antenna is not temperature
controlled. Figure 9 shows the time series of theclock offset of VLBI and the outside temperature.
It reveals that the clock offsets of VLBI are strongly
affected by the outside temperature (correlation coefficient : -0.72, lag : 2hours). Thus, for current
experiments, we have decided to monitor variationsof the reference signal through the transmission cable of the VLBI system by the Dual Mixer Time

These results suggest that it is necessary to calibrate the instrumental delay variation of the VLBI
system. In the next step, we are planning to measure the instrumental delay of the VLBI systemby the zero baseline interferometry (ZBI) method(Hama et al., 1986 [1], Yoshino et al., 1992 [8]),and we also want to replace the transmission cableby optical fibers.
4.

Summary

To compare the results of VLBI and GPS (carrier phase) frequency transfer, we have analyzed
IVS and IGS data. The results of the VLBI frequency transfer show that the stability follows a
1/τ law very closely (phase noise dominant). And
that shows the stability has reached about 2×10−11(20ps) at 1 sec. In this study, the results show that
VLBI frequency transfer is more stable than GPS
on the same baseline and same period.

27

IVS NICT-TDC News No.29

References[1] Hama, S., H. Kiuchi, Y. Takahashi, J. Amagai,
T. Yoshino, N. Kawaguchi, W. J. Klepczynski,
and J. O. Martin, Japan-U.S. Time Comparison Experiment for Realizing Better Than 1ns Accuracy by Using a Radio InterferometricTechnique, IEEE IM, 38, 2, 640–643, 1989.

Figure 9. Time series of the outside temperatureand clock offsets of VLBI.

Also, we prepared the setup on the KashimaKoganei baseline for time and frequency transfer
tests using our compact VLBI system which is currently under development. Figure 10 shows the
future image of the time transfer by the compact
VLBI system and high speed networks.

[2] Ishii, A., R. Ichikawa, H. Takiguchi, H. Kuboki,
M. Kimura, J. Nakajima, Y. Koyama, J. Fujisaku, and K. Takashima, Development of acompact VLBI system for a length examinationof a reference baseline, IVS NICT-TDC News,
No.28, 2–5, 2007.
[3] Komiyama, B., Frequency and time measurement methods, Radio Lab Bull, Vol. 29, 39–53,
1983.
[4] Kouba, J., and P. Heroux, Precise Point Positioning using IGS orbits and clock products,
GPS Solutions, No. 5, 12–28, 2001.
[5] Ray, J., and K. Senior, Geodetic techniques
for time and frequency comparisons using GPS
phase and code measurements, Metrologia, 42,
215–232, 2005.
[6] Takamoto, M., F.-L. Hong, R. Higashi, and H.
Katori, An Optical Lattice Clock, Nature, 435,
321–324, 2005.
[7] Takiguchi, H., T. Hobiger, A. Ishii, R. Ichikawa,and Y. Koyama, Comparison with GPS Time
Transfer and VLBI Time Transfer, IVS NICTTDC News, No.28, 10–15, 2007.
[8] Yoshino, T., S. Hama, and H. Kiuchi, Precise Time Comparison with Very Long Baseline Interferometry, J. of Com. Res. Lab., 39,
1, March, 1992.

Figure 10. Future image of the time transfer by thecompact VLBI system and high speed networks.

Acknowledgments: The authors would like to acknowledge the IVS and the IGS for the high quality products. We would like to thank J. Amagaiof NICT for his help with the GPS observations
and the analysis. The VLBI experiments were supported by M. Sekido, E. Kawai and H. Kuboki of
Kashima Space Research Center.

28

October 2008

Development of e-VLBI
Technologies for Ultra-rapid
UT1 Measurement
Mamoru Sekido1 (sekido@nict.go.jp),
Tetsuro Kondo1 , Jan Wagner2 ,Thomas Hobiger1 , Kensuke Kokado3 ,Hiroshi Takiguchi1 , Yasuhiro Koyama1 ,Rüdiger Haas4 , Jouko Ritakari2
and Shinobu Kurihara3
1

National Institute of Information andCommunications technology, Kashima Space
Research Center, 893-1, Hirai, Kashima,
Ibaraki 314-8501, Japan
2
Helsinki University of Technology, Metsähovi
Radio Observatory, Metsähovintie 114
FIN02540 Kylmälä, Finland
3
Geographical Survey Institute, 1 Kitasato,
Tsukuba 305-0811, Japan
4
Chalmers University of Technology, OnsalaSpace Observatory, SE-439 92 Onsala, Sweden

Abstract: Ultra-rapid UT1 measurements havebeen realized under the collaboration between
NICT, GSI(Japan), Onsala Observatory(Sweden),and Metsähvi Radio Observatory(Finland). This
achievement was made by a combination of software and hardware technologies with components
of so called e-VLBI. This paper describes the components, which contributed the Ultra-rapid UT1
measurements.
1.

Introduction

Orientation of solid Earth’s crust with respect tothe celestial reference frame is represented by polar motion and UT1. They change with time dueto the interaction between gravitational forces of
the Sun, Moon, Planets and responses of Earth’s
ocean, atmosphere, and the Earth’s interior. The
Earth orientation parameters (EOP) are still unpredictable with sufficient accuracy, although realtime use of them is required for several applications
such as spacecraft navigation.
The IERS (International Earth Rotation andReference Systems Service) and related institutes
are making efforts and contributions for quick
derivation of EOPs[7]. We have developed e-VLBI
technologies, which enable real-time or pseudo realtime VLBI observation. A pilot project for quick
measurement of UT1 by using e-VLBI has started
as a collaboration between NICT, GSI (Geographical Survey Institute, Japan), Onsala Observatory(Chalmers Univ. of Tech., Sweden), and Metsähovi
Radio Observatory (Helsinki Univ. Tech., Finland)in April 2007. Since May 2007, UT1 measurement
has become possible within 30 min. after the session. In February 2008, the fastest record of UT1
measurement within 4 minutes was achieved on
Onsala-Tsukuba baseline[4]. The key technologies
which enabled the Ultra-rapid UT1 measurement
are introduced in the following sections.
2.

e-VLBI Technologies

2.1

K5/VSSP32

NICT has developed a new PC-based VLBI dataacquisition system named K5/VSSP32[3]. This is
the second revision of K5/VSSP. Sampling rate has
been expanded up to 32 Msps and data output interface has been changed to USB(Universal SerialBus) instead of PCI-bus. One of the advantages

Figure 1.
One unit of K5/VSSP32 has 4channel input.
A variety of sampling rates(40k,100k,200k,500k,1M,2M,4M,8M,16M,32M)
and quantization bit (1,2,4,8) are available. Captured data are transfered to PC with USB(Universal
Serial Bus) interface with maximum data rates up
to 256 Mbps.
of the new system for e-VLBI is that simultaneous read/write access becomes available. Owing tothis capability, the data can be processed soon after
each scan has finished. Consequently data processing is performed during observation and the latency
of VLBI observations has been greatly reduced.
2.2

High Speed Network and High Speed
Protocol (Tsunami)

Real-time data transport from observatories in
Scandinavian countries to Japan has been realizedby high speed research network infrastructures.
Research and educational network providers NORDUnet1 and Géant22 are supporting the e-VLBI
project in Europe. The data is coming through1 http://www.nordu.net/
2 http://www.geant2.net/

29

IVS NICT-TDC News No.29

Internet23 in the USA, and to Kashima 34m telescope via JGN24 .
VLBI observations essentially require long distance data transport with high data rate. The
network path length from Scandinavian stations(Onsala, and Metsähovi) to Japanese stations(Kashima and Tsukuba) is over twenty thousands
km. TCP/IP, which is a protocol widely usedon the Internet, has not enough performance totransfer the data with a data rate over a 256Mbps
or 512Mbps over such a distance. Meiss[5] ofIndiana Univ. developed a UDP(user datagram
protocol)-based data transport protocol ‘Tsunami’for high speed file transport on high latency networks. J.Wagner and J.Ritakari at Metsähovi
observatory5 have improved and adapted it for
real-time VLBI data transfer. VLBI data output
from Mark5 formatter is captured by a PC-based
data acquisition interface card (VSIB) developedby Metsähovi[6]. Then the data are transfered bythe ‘real-time Tsunami’ software. ’Tsunami’ protocol has proven the performance of data transfer rate over 600 Mbps on the Metsähovi (Finland) - Kashima (Japan) baseline. Thanks to thehigh speed research (shared) network and realtime Tsunami protocol, observed data at Scandinavian stations are recorded in Mark5-A format[9]at Kashima in real-time. Following to the datatransfer, data format conversion and correlation
processes are automatically performed.

icy was intended to minimize the impact of failures/troubles at single task on the whole processing
scheme. Each component is designed to work independently. This allows also to maintain the components easily. Perl language was chosen because it is
TCP/IP friendly and it has large archive databaseof modules (CPAN) with a variety of functions.
The main task of the subsystem is to manage thecomputer resources and delivering jobs. Figure 2
shows an overview of the pipeline data processing
scheme for the distributed computing environment.
After correlation processing has finished, bandwidth synthesis is performed to derive precisegroup delay observables.
2.4

MK3TOOLS and UT1 Analysis

After the correlation processing, the data wereanalyzed in two ways by using VLBI analysis software CALC/SOLVE and OCCAM. The
CALC/SOLVE uses MK3 databases whereas OCCAM uses NGS cards as input of VLBI data. Hobiger et al.[1] have developed a VLBI database system based on NetCDF (network Common Data
Form)6 as a tool for storing and retrieving VLBI
data. By using the MK3TOOLS, VLBI data in either MK3 database or NGS card formats can begenerated. VLBI database for geodesy are stored
in MK3 database form in most cases, though MK3
databases have a strong dependency on computer
hardware and it has not been designed for standard
Linux systems. Therefore VLBI database handling
2.3 Software Correlator and Automaticwith MK3TOOLS has the great advantage, that
Processing
VLBI data can be manipulated on any computer
VLBI data observed at Scandinavian stations platforms.
In our ultra-rapid UT1 measurement, theare transported and recorded at the Japanese side
(Kashima or Tsukuba) in real-time. Data format MK3TOOLS have been used for the creation of
conversion from Mark5 to K5/VSSP is performed MK3 databases and NGS cards for analysis with
automatically in accordance with the observation CALC/ SOLVE and OCCAM. Automatic UT1 esschedule file. The K5/VSSP software package[2] timation scheme has been developed by T.Hobiger
has been used for the data conversion and soft- using OCCAM. Iterative ambiguity solution andware correlation. Since the modules in that pack- UT1 estimation has been performed automatiage do not have a function to communicate with cally. Manual UT1 analysis with CALC/SOLVE
each other, a simple distributed computing envi- has been also used as another way. The typical laronment has been developed. It is composed of tency of UT1 measurement is 25 min., 40min., andtask manager and job processing agents. Each 100 min. for total data rates at 128, 256, and 512of them runs as a process and communicates via Mbps, respectively. The current bottle neck of the
TCP/IP. By using such a task shared environment, data processing at high data rate is the data fordata format conversion, correlation processing, and mat conversion of raw VLBI data from Mark5 to
bandwidth synthesis procedures are performed as K5/VSSP. We are going to improve this point ina pipeline. Each component of the manager/agent the near future.
subsystem is coded by the script language Perl.
A principle for designing the task-sharing system 3. Summary
was “Minimum mutual dependency”. This polThe pilot project of Ultra-rapid UT1 measurement with e-VLBI has been operated success3 http://www.internet2.edu/
4 http://www.jgn.nict.go.jp/
5 http://www.metsahovi.fi/en/vlbi/soft-tools/

6 http://www.unidata.ucar.edu/software/netcdf/

30

October 2008

Control/communication
VLBI Data Stream
Realtime Data Transfer(Realtime-Tsunami)
Job Control Server(Cor_mgr_v2.pl)Status Monitor client(Cor_stat_monit.pl)

VLBI Database(MK3Tools)

Mark5

Bnadwidth Synthesis(komb)

Mk3 DB/NetCDF
komb dataCor
OutputFormat Conversion
Mark5 -> K5(conv_tool5.pl)Correlation Agent
Correlation Agent
Correlation Agent

Analysis(Calc/Solve,OCCAM)
UT1-UTC
resultCorrelation Agent
Correlation Agent
Correlation Agent

K5
K5
K5
K5
K5 Data
K5
K5
K5
K5

Figure 2. Automatic data processing with distributed computing environment. The software correlator
and data format converter are used fro pipeline data reduction of the VLBI data.

fully under a collaboration between Scandinavian (Onsala, Metsähovi) and Japanese (Kashima,
Tsukuba) VLBI stations. The quick UT1 measurements are enabled by international high speed network infrastructures (Géant2, JGN2, Internet2,...),
high speed data transport protocols (real-time
Tsunami), and PC-based data acquisition systems(K5,Mark5,VSIB). Computing power of personal
computer is now capable of handling raw VLBI
data by software. This leads to an improvementof compatibility of the systems and helps to boost
data conversion between different VLBI data formats. Thus mutual collaboration will be enhancedwith e-VLBI and a further expansion of VLBI networks is expected.
Acknowledgments: We are grateful to the highspeed research networks Géant2, Internet2, JGN2,
Sinet, GEMnet2 for supporting the international
collaboration on the e-VLBI project.
References[1] Hobiger, T., Y. Koyama, T. Kondo,“MK3TOOLS & NetCDF – storing VLBI
data in a machine independent array oriented
data format”, Proceeding 18th European VLBI
for Geodesy and Astrometry (EVGA) Working
Meeting April 12-13, 2007, Vienna, Austria,(http://mars.hg.tuwien.ac.at/ẽvga/), P03, 2007.
[2] Kondo, T., Y. Koyama, H. Takeuchi, andM. Kimura, “Current Status of the K5 Software
Correlator”, IVS NICT-TDC News, No. 25, pp.
23-27., 2004.
[3] Kondo, T., Y. Koyama, H. Takeuchi, andM. Kimura, “Development of a New VLBI Sam-pler Unit (K5/VSSP32) Equipped with a USB
2.0 Interface”, IVS 2006 General Meeting Proceedings(eds. Dirk Behrend & Karen Baver),NASA/CP-2006-214140, pp. 195-199, 2006.
[4] Matsuzaka, S,, K. Wada, S. Kurihara,
Y. Koyama, M. Sekido, R. Haas, and J. Wagner,“Ultra-rapid UT1 Measurements with e-VLBI”,
in Proceedings of the 5th IVS General Meeting,
St. Petersburg March 3-6, 2008.
[5] Meiss, M, “Tsunami: A High-Speed RateControlled Protocol for File Transfer”,
http://steinbeck.ucs.indiana.edu/m̃meiss/
papers/tsunami.pdf, 2004.
[6] Ritakari, J., and A. Mujunen, “Gbit/s VLBI
and eVLBI with Off-The-Shelf Components”,
International VLBI Service for Geodesy andAstrometry 2004 General Meeting Proceedings(eds. Nancy R. Vandenberg & Karen D. Baver),NASA/CP-2004-212255, pp. 182–185, 2004.
[7] Rothacher, M., D. Thaller, and R. Dill, “Analysis Coordinator”, IERS Annual Report 2005, pp.
29-31., 2005.
[8] Sekido, M., H. Takiguchi, Y. Koyama,
T. Kondo, R. Haas, J. Wagner, J. Ritakari,
S. Kurihara, and K. Kokado, ”Ultra-rapid UT1
measurement by e-VLBI”,Earth Planets andSpace, in print 2008.
[9] Whitney, A., “Mark IIIA/IV/VLBA Tape
Formats,
Recording Modes and Compatibility”, Mark IV Memo series 230A,
http://www.haystack.mit.edu/geo/mark4/memos/230.pdf, 2000.

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IVS NICT-TDC News No.29

Real-time ray-tracing throughnumerical weather models forspace geodesy
Thomas Hobiger (hobiger@nict.go.jp),
Ryuichi Ichikawa, Yasuhiro Koyama,
and Tetsuro Kondo
Kashima Space Research Center, National
Institute of Information and Communications
Technology, 893-1 Hirai, Kashima, Ibaraki
314-8501, Japan
Abstract: Numerical weather models have undergone an improvement of spatial and temporal resolution in the recent years, which made theiruse for space geodetic applications feasible. Raytracing through such models permits the computation of total troposphere delays and ray-bending
angles. At the National Institute of Information
and Communications Technology (NICT) the socalled KAshima RAy-tracing Tools (KARAT) havebeen developed which allow to obtain tropospheredelay corrections in real-time. Together with finemesh weather models from the Japanese Meteorological Agency (JMA) huge parts of the East Asian
region, including Japan, Korea, Taiwan and East
China, can be covered. Thus a short overview
about the capabilities and functions of KARAT
will be given and computation performance issues
will be discussed. The ray-traced total troposphereslant delays can be used as a correction of space
geodetic data on the observation level. Additionally, an overview will be given about the upcoming
on-line service, which permits the reduction of troposphere delays from user-submitted data.
1.

Introduction

The introduction of new mapping functions(e.g. Niell (1996[7],2001[8]), Boehm et al.(2006a[1],2006b[2])) in the recent years significantly improved space geodetic techniques. Although modern mapping functions are derived from numerical
weather models the information from such meteorological data-sets is reduced to a few time- andlocation-dependent coefficients which relate slanted
troposphere quantities to equivalent zenith measures. Moreover, the spatial variations of the troposphere above each station have to be estimated in
the analysis process in the form of gradient parameters. As numerical weather models of regional size
have undergone an improvement of accuracy andprecision it became feasible to utilize ray-traced
troposphere slant delays directly for the geodetic
analysis of space geodetic techniques.

Figure 1. The spatial domain for which JMA mesoscale weather models are available.
1.1

Mesoscale analysis models from the
JMA

The Japanese Meteorological Agency (JMA)
provides a variety of weather models ranging fromglobal models to fine-mesh models which coveran area of only a few tens of kilometers. The
meso-scale 4D-Var model (i.e. Meso-scale Analysis Data (MANAL)) from JMA (JMA(2002)[6],
Ishikawa(2001)[5]) with its horizontal resolution of
about 10km was found to have the best trade-off
between grid-spacing and area size. This model
covers large parts of Eastern Asia, including Japanand its Southern islands, Korea, Taiwan and Eastern China (figure 1). Moreover, the three hourtime-resolution of the data-sets makes the appliance of this model for positioning applications feasible.
2.

Kashima ray-tracing tools (KARAT)

Based on the requirement to deliver ray-traced
delays in real-time (assuming that numerical
weather models are available as forecast data) a setof tools have been created in order to carry out the
ray-tracing tasks. Coding in C++ does not only
permit to design the modules close to machine language, but also allows to interface external classes
which enable multi-core/multi-processor support.
A detailed description about KARAT and its performance can be found in Hobiger et al. (2008b)[4].
2.1

Preparing the data

Since the grid points of the JMA mesoscale
weather models are not equally spaced on a geographic coordinate system it is necessary to interpolate them on a rectangular grid. Moreover, it ismandatory to transform the geopotential heights,
which are used by the meteorologists, into geometric heights, which can be used for ray-tracing calcu-

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October 2008

Figure 2. The three ray-tracing modes of KARAT together with their accuracy and speed performance.

lations. Thus, the first tool of KARAT handles all
this tasks, using a sophisticated interpolation algorithm which allows to compute refractivity values
on a geographic grid with user-defined boundaries,
resolution and height steps. Each epoch of the numerical weather model is processed by this tool andbinary files are created for follow-on processing. As
described by Hobiger et al. (2008b)[4], a dedicatedheight system helps to reduce the number of necessary height levels without accuracy degradationof the ray-traced slant delays.
2.2

The ray-tracer

The main module of KARAT is the ray-tracing
engine which reads consecutive binary weathermodels, covering a 24 hours period and loads the refractivity fields into free memory. Once all the data
is put to memory, ray-tracing cores can be launchedindependently. Each core is at idle status until station position and ray-geometry (i.e. time, azimuthand elevation angles) are parsed to it. As KARAT
uses OpenMP (e.g. Quinn(2004)[9]) to take advantage of multi-core and multi-processor architectures, the number of available ray-tracing cores isonly limited by the number of CPU cores whichshare the same memory. KARAT offers three different modes (figure 2) in which the ray-tracing canbe carried out.
he fastest, but least accurate one assumes linear ray-propagation between two height levels andcomputes the refraction when the ray-crosses alayer. The more advanced mode, considers thatthe ray is also bended when propagating between
two levels. This mode is called Thayer, named after the corresponding paper by Thayer (1976)[10].
Both modes fully consider the 3D refractivity field,
but don’t allow for out-of-plane propagation of theray. The most sophisticated, but also slowest mode
solves the Eikonal equation numerically and pro-vides the 3D ray-path together with the total delay. As the differences between the Thayer andthe Eikonal model hardly exceeds the mm-level atlowest elevations (3 degrees) the Thayer mode isoften selected as a compromise between speed andaccuracy.
The ray-tracing module allows to handle geometry files (i.e. text files containing site positions,
epochs, azimuth and elevation angles) or reads
RINEX files and computes the observing geometry
using IGS orbit information. Moreover the reduction of troposphere delays is supported by correcting code and phase measurements directly in the
RINEX files.
2.3

Supporting tools

Beside the main modules described above,
KARAT includes smaller tools for the manipulation of (binary) numerical weather models as well
as scripts for orbit calculations and display of theresults. It is planned for the future that an additional module will manage large ray-tracing jobs
and distribute the work-load on several ray-tracing
clients.
3.

Ray-traced tropospheregeodesy - first results

for

space

Hobiger et al. (2008a)[3] have analyzed theimpact of ray-traced troposphere delays on precise point positioning with GPS. As the numerical weather models currently don’t allow to obtain mm-accurate slant troposphere delays, it wasnecessary to estimate a residual troposphere delay,
when using ray-traced data-sets. Station heightrepeatabilities of several GPS sites in East Asia
could be improved when KARAT data has beenused. Moreover the RMS of the residuals were
found to be at the same levels as those obtained

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IVS NICT-TDC News No.29

Figure 3. Flow chart of the KARATS processing
chain. KARATS will subtract troposphere delays
from the user’s observation based on the geometry
computed from precise orbits(GNSS) or source positions (VLBI).
from modern mapping functions and gradient estimation. Additionally, the authors could show that
positioning solutions with cm-range accuracy could
be achieved when the ray-traced data was analyzed
without residual troposphere estimation.
In order to apply such corrections to VLBI
measurements it is necessary that both stations
are either within the same high-resolution weathermodel or that several regional numerical weathermodels are used to consider the weather conditions
at each site. Although KARAT is currently only
dealing with meso-scale data from JMA it is possible to handle numerical weather models from other
weather agencies. Tests with ray-traced troposphere slant delays for East Asian VLBI networks
are planned for the close future.
4.

Kashima ray-tracing service (KARATS)

In order to enable users of space geodetic techniques to take advantage from KARAT without
the need to access numerical weather models by
their own it was decided to provide ray-tracing asa service. Thus the ray-tracing tools will be embedded in an automatic processing chain, called
Kashima Ray-Tracing Service (KARATS), which
can be started via a web-interface. Figure 3 shows
how KARATS is expected to operate. Once auser (from the GPS or VLBI community) has
taken his observations, he can send the data in acommon format (which will be RINEX for GPS
and MK3/FITS for VLBI at first) via Internet
to KARATS. Thereafter the web-server will do arough data-check and compute the geometry fromthe observation file. As soon as a ray-tracing client
becomes available it will send the geometry file tothat machine. The client performs the ray-tracing
through the weather model and sends the tropospheric delays back to the server. Thereafter the
ray-traced delays are subtracted from the user’s
data and a ”reduced” observation file is sent backto the user. Thus the analyst can estimate histarget parameters without spending too much effort on estimating tropospheric delays. In the casethat VLBI observations are submitted it is checkedthat both stations lie within the boundaries of the
NWM and thereafter the tropospheric delays arecomputed at each station. In a final step the server
will compute the differenced corrections and apply
them to the VLBI observations.
Moreover it is planned to run KARATS for realtime applications. Since this mode needs weather
prediction data from the JMA it will be limited to aselected user group. The KARATS post-processing
mode will be free of charge and a turn-around timeof one minute per (RINEX) file is anticipated.
Acknowledgments: The first author wants to thankthe Japanese Society for the Promotion of Science(project P06603) for supporting his research.
References[1] Boehm, J., A. Niell, P. Tregoning, and H. Schuh(2006a), Global Mapping Function (GMF): A
new empirical mapping function based on numerical weather model data, Geophys. Res.
Lett., 33, L07304, doi:10.1029/2005GL025546.
[2] Boehm, J., B. Werl, and H. Schuh (2006b),
Troposphere mapping functions for GPS andvery long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data, J. Geophys.
Res., 111, B02406, doi:10.1029/2005JB003629.
[3] Hobiger T., R. Ichikawa, T. Takasu, Y. Koyama
and T. Kondo (2008a), Ray-traced troposphereslant delays for precise point positioning, Earth,Planets and Space, 60, e1–e4.
[4] Hobiger T., R. Ichikawa, Y. Koyama and T.
Kondo (2008b), Fast and accurate ray-tracing
algorithms for real-time space geodetic applications using numerical weather models, J.
Geophys. Res., doi:10.1029/2008JD010503, inpress.
[5] Ishikawa, Y., Development of a mesoscale 4dimensional variational data assimilation (4DVar) system at JMA, Proceedings of the 81st
Annual Meeting of the AMS: Precipitation Extremes: Prediction, Impacts and Responses,
P2.45, 2001.

October 2008[6] JMA, Outline of the operational numerical
weather prediction at the Japanese Meteorological Agency, 158pp, 2002.
[7] Niell, A. E. (1996), Global mapping functions
for the atmosphere delay at radio wavelengths,
J. Geophys. Res., 101(B2), 3227–3246.
[8] Niell, A. E. (2001), Preliminary evaluation of
atmospheric mapping functions based on numerical weather models, Phys. Chem. Earth,26, 475–480.
[9] Quinn, M. J. (2004), Parallel Programming in
C with MPI and OpenMP, McGraw-Hill Inc,.
[10] Thayer, G. (1967), A rapid and accurate ray
tracing algorithm for a horizontally stratified
atmosphere, Radio Science, 1, pp. 249–252.

Figure 4. Logo of KARATS.

34

“IVS NICT Technology Development Center News” (IVS NICT-TDC News) published by the
National Institute of Information and Communications Technology (NICT) (former the Communications Research Laboratory (CRL)) is the continuation of “IVS CRL Technology Development
Center News” (IVS CRL-TDC News). (On April 1, 2004, Communications Research Laboratory(CRL) and Telecommunications Advancement Organization of JAPAN (TAO) were reorganized
as “National Institute of Information and Communications Technology (NICT)”.)
VLBI Technology Development Center (TDC) at NICT is supposed
1) to develop new observation techniques and new systems for advanced Earth’s rotation
observations by VLBI and other space techniques,2) to promote research in Earth rotation using VLBI,
3) to distribute new VLBI technology,4) to contribute the standardization of VLBI interface, and5) to deploy the real-time VLBI technique.
The NICT TDC newsletter (IVS NICT-TDC News) is published annually by NICT.

This news was edited by Tetsuro Kondo and Yasuhiro Koyama, Kashima Space Research Center,
who are editorial staff members of TDC at the National Institute of Information and Communications Technology, Japan. Inquires on this issue should be addressed to Y. Koyama, National
Institute of Information and Communications Technology, 4-2-1, Nukui-kita, Koganei,Tokyo 1848795, Japan, TEL : +81-42-327-7557, FAX : +81-42-327-6834, e-mail : koyama@nict.go.jp.
Summaries of VLBI and related activities at the National Institute of Information
and Communications Technology are on the Web.
The URL to view the home
page of the Space-Time Measurement Project of Space-Time Standards Group is :“http://www.nict.go.jp/w/w114/stmp/index e.html”.

IVS NICT TECHNOLOGY DEVELOPMENT CENTER NEWS No.29, October 2008
International VLBI Service for Geodesy and Astrometry
NICT Technology Development Center News
published by
National Institute of Information and Communications Technology, 4-2-1 Nukui-kita, Koganei,
Tokyo 184-8795, Japan