GSI Japan - 21st of June 1999 GPS-Positioning using Virtual Reference Stations - Theory, Analysis...
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Transcript of GSI Japan - 21st of June 1999 GPS-Positioning using Virtual Reference Stations - Theory, Analysis...
GSI Japan - 21st of June 1999
GPS-Positioning using Virtual Reference Stations -
Theory, Analysis and Applications
Herbert Landau Herbert Landau Spectra Precision Terrasat GmbHSpectra Precision Terrasat GmbH
Overview
Principle of Virtual Reference Stations Principle of Virtual Reference Stations Modelling of Error Sources Modelling of Error Sources Hardware Setup Hardware Setup Software SetupSoftware Setup Implementations - ReferencesImplementations - References Results of RTK Positioning AnalysisResults of RTK Positioning Analysis
Why Virtual Reference Stations?
Improvement of accuracy versus classical RTKImprovement of accuracy versus classical RTK Reliability improvementReliability improvement Productivity improvement Productivity improvement Local reference station is obsoleteLocal reference station is obsolete Positions are automatically derived in a precise Positions are automatically derived in a precise
geodetic reference station system geodetic reference station system Real-time service for ionospheric disturbances can be Real-time service for ionospheric disturbances can be
provided to the user provided to the user
Concept of Virtual Reference Stations (VRS)
A D
C
B
Rover
Virtual Ref.
Modeling systematic Modeling systematic errorserrors
Elimination of errorsElimination of errors Generation of Generation of
interpolated interpolated observations for observations for virtual station virtual station
Real-Time: RTCMReal-Time: RTCM Post-Mission: Post-Mission:
RINEXRINEX
Data Flow in the Network
Reference Station
Reference Station
Reference Station
Reference Station
Raw Data
GPSNetwork
Router
Data Flow in the Network
Reference Station
Reference Station
Reference Station
Reference Station
Raw Data
GPSNetwork
Router
Rover
Data Flow in the Network
Reference Station
Reference Station
Reference Station
Reference Station
Raw Data
GPSNetwork
Router
NMEA Position
Data Flow in the Network
Reference Station
Reference Station
Reference Station
Reference Station
Raw Data
GPSNetwork
Router
NMEA Position
Data Flow in the Network
Reference Station
Reference Station
Reference Station
Reference Station
Raw Data
GPSNetwork
Router
Virtual Ref. Station
RTCM
NMEA Position
Data Flow in the Network
Major Error Sources in Differential-GPS
IonosphereIonosphereTroposphereTroposphere Error in Error in
Satellite OrbitSatellite Orbit
Tropospheric Modelling
Modified Hopfield Model Ground meteorological measurements not sufficient Water Vapour Radiometers are too expensive Elimination of tropospheric errors is required for
ambiguity resolution in the network Determination of a model scale factor
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
00:00 05:00 10:00 15:00 20:00 25:00 30:00 35:00 40:00 45:00
Tropospheric Scale Factor Convergence on the Network Stations
Minutes
Sca
le fa
cto
r of
fse
t
Improvement due to Tropospheric Scaling in the Bysat Network
020406080
100120140160180200
Erro
r [m
m]
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80
Elevation
Max. w/o
Max. with
RMS w/o
RMS with
Ionospheric Modelling
Single layer model Determination from L1/L2 carrier phase data All data of all stations The correction by the model is applied to the
observations This is required for wide lane ambiguity fixing
Average yearly number of sun spots
0
50
100
150
200
1960 1970 1980 1990 2000
RZ
25
20
15
10
5
0
19701960 1980 1990 2000
Year
Ionospheric error in GPS L1
Err
or
[m]
Solar Cycle and Ionosphere
Ionospheric Maximum in 2000/2001
1995 1995,5 1996 1996,5 1997 1997,5 19991998 1999,51998,5 2000 2000,5
5
10
15
20
25
30
35
Time (Years)
Mea
n T
EC
(T
EC
U)
CODE Ionospheric model Station Zimmerwald, CH
CODE Ionospheric model Station Zimmerwald, CH
0.06
0.05
0.04
0.03
0.02
0.01
0.00
-0.01
-0.02
-0.03
-0.04
-0.05
-0.0613:00 13:10 13:20 13:30 13:40 13:50 14:00
Local Time
Err
or in
Met
er
Differential Ionosphere Dec. 1998 on 70 km Baseline
Local Time
Err
or in
Met
er
13:00 13:10 13:20 13:30 13:40 13:50 14:00
0.25
0.20
0.15
0.10
0.05
0.00
-0.05
-0.10
-0.15
-0.20
-0.25
Differential Ionosphere Feb. 1999 on 70 km Baseline
Local Time
Err
or in
Met
er
13:00 13:10 13:20 13:30 13:40 13:50 14:00
0.50
0.40
0.30
0.20
0.10
0.00
-0.10
-0.20
-0.30
-0.40
-0.50
Differential Ionosphere Feb. 2000 on 70 km Baseline
Satellite Orbits
Starting with broadcast ephemeris Additional use of predicted ephemeris Comparison of broadcast and predicted ephemeris Typical differences < 10 m Differences of up to several 100 m can be found
during satellite maneuvers Satellites with large differences are not used Estimation of residual error
Integrity Monitoring
Outlier detection in pseudo-ranges Continuous navigation solution for all stations Continuous DGPS solution for all stations
In case of outliers the epoch will not be used
Network Processes
Geometric correction Correction for tropospheric errors Correction for ionospheric errors Correction for multi-path Ambiguity resolution Consistency check
Derivation of Corrections
Estimation of corrections from residuals in L1 and L2 carrier phase measurements
Correction in North-South and East-West direction for each satellite for geometrical part (troposphere and ephemeris),
typical < 2 ppm ionospheric part, typical < 15 ppm
Computation of corrections performed once per second
Computation of VRS-Data
Starting with the data of the reference station nearest to the rover
Geometric displacement of these data to the virtual position
Applying the corrections for the geometric and the ionospheric parts
Transmission of the VRS data via mobile-phone in RTCM Standard with messages 3, 18, 19
Data Communication
M o d e m
M o d e m
M o d e m
R o u te r
M o d e m
M o d e m
M o d e m
M o d e m
M o d e m
G P S N e tw o rkA c c e ss S e rve r
LA N
LA N
R o ve r
R o ve r
R o ve r
GSM Mobile Phone
R e fe re n zsta tio n e n K o n tro llze n tru m
Software Structure Ref.Stn.Ref.Stn. Ref.Stn. Ref.Stn.
Receiver Interfaces, RINEX Storage, Antenna Phase Center Correction
Synchronizer, Virtual Ref. Station Processor, Ephemeris, Ionosphere andTroposphere modeling
Interpolator
RTCMGenerator
Communication
Module
Position
Mobile Phone
PositionRTCM
Interpolator
RTCMGenerator
Communication
Module
Interpolator
RTCMGenerator
Communication
Module
Mobile Phone
PositionRTCM
Mobile Phone
PositionRTCM
Raw Data
Neufahrn
The Bysat Network in Germany
Weinstadt
Münsingen
Gerstetten
Untereichen
Augsburg
Höhenkirchen
Mainburg
Mühldorf
Ashtech 9 Stations 50-70 km Telekom Net Router Access Server
Performance Analysis in the Bysat Network
HöhenkirchenHöhenkirchen
MainburgMainburg
70 km
AugsburgAugsburgMühldorfMühldorf
RoverNeufahrn
- Data of February 2000Data of February 2000- 90 hours day/night 90 hours day/night - Rover in Neufahrn, 32 kmRover in Neufahrn, 32 km from Höhenkirchen from Höhenkirchen
Comparison of Standard RTK with VRS-RTK
Recorded data of Dec. 6th, 1999 13:30-15:12 local time on rover station Neufahrn
VRS data generated in real-time was recorded Post-processing with Geotracer RTK-Software on PC Automatic OTF search with intervals of 15 seconds Sequential adding of data until ambiguity resolution is
successful
Improvement in Time to Fix by using VRS
0
10
20
30
40
50
60
70
80
Num
ber o
f Fix
es
0.0 60.0 110.0 160.0 210.0 265.0
Initialisation Time [Sek]
Standard RTK
VRS
Real-Time Test Setup in the Bysat Network
Operation of rover Neufahrn (32 km from the nearest reference station) with Geotracer RTK system
After each fix the Geotracer RTK system outputs position data for 30 seconds
After that the RTK system initializes the ambiguity search again, no data from the past is used
All position output is stored on an extra PC and analyzed statistically
Error in North – 32 km Baseline
0
1000
2000
3000
4000
5000
6000
Num
ber
of P
ostio
ns
-50 -40 -30 -20 -10 0 10 20 30 40 50
Error [mm]
Confidence LevelConfidence Level90 %: < 13 mm90 %: < 13 mm99 %: < 26 mm99 %: < 26 mm
Confidence LevelConfidence Level90 %: < 13 mm90 %: < 13 mm99 %: < 26 mm99 %: < 26 mm
Error in East – 32 km Baseline
0100020003000400050006000700080009000
Num
ber o
f Pos
ition
s
-50 -40 -30 -20 -10 0 10 20 30 40 50
Error [mm]
Confidence LevelConfidence Level90 %: < 9 mm90 %: < 9 mm99 %: < 21 mm99 %: < 21 mm
Confidence LevelConfidence Level90 %: < 9 mm90 %: < 9 mm99 %: < 21 mm99 %: < 21 mm
Error in Height – 32 km Baseline
0
500
1000
1500
2000
2500
3000
Num
ber
of P
ositi
ons
-50 -40 -30 -20 -10 0 10 20 30 40 50
Error [mm]
Confidence LevelConfidence Level90 %: < 25 mm90 %: < 25 mm99 %: < 49 mm99 %: < 49 mm
Confidence LevelConfidence Level90 %: < 25 mm90 %: < 25 mm99 %: < 49 mm99 %: < 49 mm
RTK Initialisation – 32 km Baseline
0
2
4
6
8
10
12
Perc
ent
0 20 40 60 80 100 120 140 160 180 200
Initialisation Time [sec]
PerformancePerformance
50 %: < 40 sec50 %: < 40 sec90 %: < 80 sec90 %: < 80 secaverage: 58 secaverage: 58 sec
PerformancePerformance
50 %: < 40 sec50 %: < 40 sec90 %: < 80 sec90 %: < 80 secaverage: 58 secaverage: 58 sec
Bysat Network – 32 km : 11AM – 4PM
0
50
100
150
200
250
Num
ber
of p
ositi
ons
-50 -40 -30 -20 -10 0 10 20 30 40 50
Error in North [mm]
0
50
100
150
200
250
300
350
400
Num
ber
of p
ositi
ons
-50 -40 -30 -20 -10 0 10 20 30 40 50
Error in East [mm]
0
50
100
150
200
250
Num
ber
of p
ositi
ons
-50 -40 -30 -20 -10 0 10 20 30 40 50
Error in Vertical [mm]
0
2
4
6
8
10
12
14
Perc
ent
0 50 100 150
Initialisation Time [sec]
90 % < 17 mm90 % < 17 mm
99 % < 37 mm99 % < 37 mm
90 % < 17 mm90 % < 17 mm
99 % < 37 mm99 % < 37 mmAverage Average
60 seconds60 seconds
Average Average
60 seconds60 seconds
Conclusion GPS-Network successfully creates improved VRS RTCM GPS-Network successfully creates improved VRS RTCM
corrections in real-timecorrections in real-time
VRS reduces systematic errors substantially, but cannot eliminate VRS reduces systematic errors substantially, but cannot eliminate them completely them completely
VRS allows to do RTK positioning at distances a standard RTK VRS allows to do RTK positioning at distances a standard RTK system never will reachsystem never will reach
Virtual Reference Stations improve:Virtual Reference Stations improve:
AccuracyAccuracy
Productivity via shorter Time to FixProductivity via shorter Time to Fix
Reliability Reliability