Introduction ofQZSS correction service
1/12/2022 at ICG Training
Nobuaki Kubo, Kaito Kobayashi, Tomohiro Ozeki, Hirotaka Kanamori (TUMSAT)University and Laboratory• Tokyo University of Marine Science and Technology• Marine Technology and Marine Science• Information and communication engineering laboratory(GPS/GNSS lab.)• Staff 2 + Graduate 6 + Undergraduate 6 + Visiting Researcher 2Research Subjects at our lab.
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Automobile navigation
Ship navigation
Railway navigation
Machine control
Pedestrian navigation
SurveyUAV applications
GNSS Simulation

Applications• Static and Kinematic Precise Positioning• Multipath mitigation• Software GNSS
• GNSS simulation using 3D map• Indoor positioning• Precise orbit determination• GNSS/other sensors integration

Technologies behind applications
If you are interested in GNSS,
we are welcome for your join our school.

Contents• Brief Introduction of GNSS positioning• Test results of QZSS correction services-RTK vs. QZSS CLAS/SLAS/PPP-long term test of PPP in 7 countries

Error Sources on the GNSS measurements
SourcesPotential error size

Satellite clock errors

Broadcast : -5 ns (rms)
Precise: -75 ps (rms)

Satellite orbital errors

Broadcast : -2 m (rms)
Precise: -5 cm (rms)

Ionospheric errors

2-10 m (at zenith direction)

Tropospheric delay
Multipath (open sky)
Receiver Noise

2.3-2.5m (at zenithdirection)
Code : 0.5-1 m
Carrier : -5 cm
Code : 0.25-0.5 m (rms)
Carrier : 1-2 mm (rms)Improved GNSS (relative positioning)• DGNSS and RTK are powerful method for error mitigation.
• They use the fact that the most of error sources change slowly in thetime domain if the distance between reference and user is approx.
within 10-100km.
• Please remember that differential technique provides only vector
solution from base station to the target position → precise positionof base station should be prepared.
(x ,y ,z)Target position(dx,dy,dz) can be estimated.

(xref ,yref ,zref)
Base station

PPP (Precise Point Positioning)• We discussed about relative positioning to cancel the common errors.
• We switch from relative positioning to point positioning. Basically base station
is not required for users.
• We need to consider the measurement errors more in details if we want tohave centimeter-level accuracy in the point positioning.

(x ,y ,z)Target position(xref ,yref ,zref)
Base station

Accuracy (95%)
SPP ： 1.36 m
DGNSS ： 0.44 m
RTK ： 0.003 m
PPP :0.081 m

SPP, DGNSS, RTK, PPP (open sky)
4

30.01

SPP 1H

20.00510-4-3-2-1

01

2

3

40-0.01-0.00500.0050.01-1DGNSS 1H-0.005-2-3-0.01

RTK 1H-4MADOCA-PPP 24H(after conversion)Different environments for GNSS

Tunnel and indoor
1. Impossible…
Countryside
1. cm-level
2. Low-cost

It is important to switch algorithm smoothly
depending on the condition…

Urban
1. Decimeter-level
2. Low-cost
3. Multi-sensors

Typical characteristics Only RTK requires near base station
CLAS(PPP-RTK)

PPP

Sat orbital〇〇

Sat clock

〇

〇

Iono

〇

△（next）

Tropo〇

Error/service

SLAS(DGNSS)

Not separated

Convergence

RTK

Not separated

InstantInstant-1 min.

15-30 min.

CoverageJapan

Within about 3050 km

JapanNo limitation

Measurements

CodeCarrier

CarrierCarrier

CORS(continuously operating reference stations)• In some regions, GNSS CORS networks
are so well developed and dynamic thatthey have a more prominent role thanthe existing classical passive geodetic
infrastructure in reference frame
determination or monitoring.
• Even commercial company started to
install many base stations for precise
positioning services.
• It means that GNSS based
survey/navigation has a potential for
more reliable/safety applications

Approximately 1,300 stations

Ichimill (SoftBank starts RTK service in 2019)
3,300 base stations

GNSS + LTE + internal Ant.
All you need is switching on…
About $50/month. We can use
RTK in everywhere in Japan aslong as Softbank LTE is available.

Japanese territory (land) : 378,000 km2
378,000/3,300 = 114 km2
Very dense

The advent of very good lowcost multi-GNSS dual-frequency
GNSS receiver.
Strong RTK engine !

Pro Pilot 2.0 and Eyesight X• Nissan and Subaru for now.
• CLAS service is used.
• Precise 3D MAP is used.
• This map has been generated using RTK.

ARIYALEVORGQZSS Overview -SystemRanging Signals of QZSSSignalFrequency
MHzL1C/A
L1C
L1SService✓✓✓✓✓✓✓✓✓

Short Messaging✓✓✓

Augmentation(SBAS) SBAS (L1) Service--✓

Positioning
Positioning

1575.42

Complement GPS
Complement GPS
DGPSAugmentation(SLAS) Code Phase
Positioning(Messaging
L1Sb
L2C
L5 I/Q
L5S

1227.60
1176.45

L6D)

Positioning

Complement GPS✓✓✓

Positioning

Complement GPS✓✓✓

Experimental(L5 SBAS) L5 SBAS (DFMC)
PPP-RTK
Augmentation(CLAS)

-✓✓

✓

✓

✓

PPP, PPP-AR-✓✓(Carrier Phase Positioning)

1278.75
L6E

QZS-1 QZS-2/4 QZS-3
IGSO
IGSO
GEO

CompatibilityExperimental(MADOCA)(Carrier Phase Positioning)

Provided by CAOSLAS Service▌Service Area of SLAS

monitoring station:
SapporoSendai
Hitachi-ohta
Komatsu
KobeHiroshima
Fukuoka
Tanegashima
Amami
ItomanMiyako-jimaIshigaki-jima
Chichi-jima▌Accuracy of SLAS

Service Area is the area surrounded by the red line.
The left-axis is latitude, and lower-axis is longitude.

positioning errorm(95%)
horizontal
vertical≤ 1.0 m≤ 2.0 mRemarks

EL mask : 10°
User range error caused by user’s receivers
and user’s situation : 0.87 m(95%)

35.6663343

139.79220132

Trimble NetR9 (TUMSAT)
6/3/2021 24H

u-blox F9P (TUMSAT)
6/13/2021 24H
トリンブルアンテナ＋u-blox F9P受信機
SLAS測位率：100%※赤点線が真値から1m(公称水平精度 95%値)※真値はF3解より算出
Lat=35.66634193、Lon=139.79220106、Hight=59.81

CLAS Service
Centimeter Level Augmentation Service: CLAS

QZSS
Ground Segment
L6⚫ Carrier phase positioning, PPP-RTK⚫ RTCM SSR uses for OSR calculation⚫ H 6.0 cm (95%), V 12.0 cm (95%)⚫ Domestic, land service
Centimeter class Augmentation
Data L6 (2000 bps)

GNSS EarthObservation
Network(GEONET)
Augmentation
Data Generation

Precise Survey

IT Construction

IT Agriculture

Real-time Users (cm level accuracy)

CLAS : Core AsteRx4 (TUMSAT)
6/13/2021 24H
トプコンアンテナ＋CORE AsteRx4受信機
Fix率：99.6%※赤点線が真値から6cm(公称水平精度 95%値)※真値はF3解より算出
Lat=35.66634193、Lon=139.79220106、Hight=59.81

Test results at real construction site
・KOMATUS製の重ダンプの運転席天井にNovAtelアンテナを設置。新東名の盛り土作業の連続運用中
・運転席横の補助座席に4分配、受信機、PC等々を設置
・データ取得は9時～15時(JST) 10時過ぎにsimを交換
・測位間隔は5Hz

RTK results (horizontal)

Removal of sandBring the sand->Height of the car sinks

Removal of sand->Height of the car rises

Bring the sand

RTK results (LLH)

DocomoSoftbank

CLAS results (LLH)

Fix率：100%

Comparison between RTK and CLAS

MADOCA-PPP（GPAS）
GPAS aspires to be a company that contributes to the realization and prosperity of a safer,more secure and more comfortable society by providing highly accurate positioning services
at anytime and from anywhere in the world.

PPP : u-blox F9P (TUMSAT)
6/13/2021 24H
u-blox F9P+GPAS PPP correction

After convergence※真値はF5解より算出
Lat=35.6663344、Lon=139.7922013、Hight=59.746

RTKNAVI PPP-how to setGPASMADOCA PPP Performance evaluationin Asia and Oceania• The first objective is to evaluate real
MADOCA PPP performance in several
countries in Asia and Oceania.
• Receiver is multi-GNSS receiver
manufactured by Magellan Systems Japan.
• The second objective is to find the potential
users of PPP in these countries.

Issues in sea and undeveloped area

It is difficult to use cm-level accuracy on the sea andundeveloped areas without controlled base stations.

PPP is possible through the satellite

No limitation in baseline

20km~30km (RTK)
基地局

Outline of locations
Locations (Time)TUMSAT JAPAN（August 2019）
Chula Thailand（August 2019）
UOP Philippine（August 2019）
MJIIT Malaysia（Nov. 2019)
Curtin Australia（Nov. 2019）
UOI Indonesia（Dec. 2019）
Singapore：（Feb. 2021）
Vietnam：（）ThailandTokyo

Australia→←Malaysia

1,Apr,2020,real time (Thailand)Average absolute horizontal error for each countries (April)
0.35

0.3

0.25

0.2

0.15

0.1

0.05

0
3月30日

4月4日

4月9日

4月14日
日本

UPThailand

4月19日
MJIITIndonesia

4月24日
Curtin

4月29日

5月4日

mHorizontal STD for each countries (April)

0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
3月30日

4月4日

4月9日

4月14日
日本

UP

Thailand

4月19日
MJIIT

Indonesia

4月24日
Curtin

4月29日

5月4日

http://www.denshi.e.kaiyodai.ac.jp/gnss_tutor/madoca.html

Comparison between low-cost and high-end
kinematic mode : GPS/GLO/QZSS (IGS final), TUMSAT

F9P

NetR9

SLAS/CLAS/MADOCA comparison
at the same timeBrief test at Iwaki farm
RTK vs. SLAS/CLAS/MADOCA-PPP

GPS-703-GGG-HV5m
Lighthouse受信機

4 splliter

DC Truth5m

F9P(SLAS)
5Hz

F9P(rawx)
5Hz

AsteRx4 5Hz
CLAS

MADOCA-PPPTest environment

Plow a field for soybeans

10-20cm required
SPP ×SLAS △Temporal base station

CLAS/MADOCA 〇https://agri-info-design.com/agribus-navi-2/

Post-processed RTK
Fix rate：100%

Origin : base station was set.

RTKLIB_b33でリファレンス位置を生成(解析条件：GQEB、15度、35dB、Fix and Hold)
解析時間：5時29分45秒～6時11分0秒(GPSTIME)SLAS

Horizontal errors

LLH
errorsSLAS 100%

CLAS

Horizontal errors

Fix rate：100%

LLHerrorsMADOCA-PPP

Horizontal errors

LLHerrors
100%

CLAS at highway(continuously about 100 km)
Horizontal difference
Softbank RTK
94.5% FIX
based on geodetic survey solutions
100㎞

Core AsteRx4 CLAS
79.5% FIX
based on F3 solutions

There is an artificial difference between
geodetic survey solutions and F3 solutions

tethering 〇Switching base station 18 times

E-W 27cm N-S -12cm H 3cm at TUMSATDo you have any questions ?
nkubo@kaiyodai.ac.jp

PPP-RTK and PPP-AR• First of all, CLAS is assumed one of the PPP-RTK method.
• As you can see slide 10, both CLAS(PPP-RTK) and PPP are same in that error
sources are separated such as precise sat clock, precise orbit, andatmospheric errors. It is called SSR (state space representation). As fornormal DGNSS/RTK, it is called OSR (observation space representation).
• Then, PPP-RTK normally uses double-difference technique to resolve carrier
phase ambiguities. And last, PPP-RTK resolves ambiguities. Therefore, we see
FIX or not FIX in PPP-RTK.
• On the other hand, PPP does not use double-difference technique. We will
wait for convergence of errors especially for ionospheric error. Therefore,wee don’t see FIX or not FIX in PPP.
• However, PPP also can resolve carrier phase ambiguities with FCB (fractionalcycle bias) and it is called PPP-AR. If we have better estimated ionosphericerrors, convergence time is greatly reduced.
• PPP-RTK and PPP-AR have different approaches into ambiguity resolution
but it seems to be the performance of both will be close.