1. GSI Japan - 21st of June 1999 GPS-Positioning using Virtual Reference Stations - Theory, Analysis and Applications Herbert Landau Spectra Precision Terrasat GmbH

2. Overview  Principle of Virtual Reference Stations  Modelling of Error Sources  Hardware Setup  Software Setup  Implementations - References  Results of RTK Positioning Analysis

3. Why Virtual Reference Stations?  Improvement of accuracy versus classical RTK  Reliability improvement  Productivity improvement  Local reference station is obsolete  Positions are automatically derived in a precise geodetic reference station system  Real-time service for ionospheric disturbances can be provided to the user

4. Concept of Virtual Reference Stations (VRS) A D C B Rover Virtual Ref.  Modeling systematic errors  Elimination of errors  Generation of interpolated observations for virtual station  Real-Time: RTCM  Post-Mission: RINEX

5. Data Flow in the Network

6. Reference Station Reference Station Reference Station Reference Station Raw Data GPS Network Router Data Flow in the Network

7. LAN Reference Station Reference Station Reference Station Reference Station Raw Data GPS Network Router Rover Data Flow in the Network

8. LAN Reference Station Reference Station Reference Station Reference Station Raw Data GPS Network Router NMEA Position Data Flow in the Network

9. LAN Reference Station Reference Station Reference Station Reference Station Raw Data GPS Network Router NMEA Position Data Flow in the Network

10. LAN Reference Station Reference Station Reference Station Reference Station Raw Data GPS Network Router Virtual Ref. Station RTCM NMEA Position Data Flow in the Network

11. Major Error Sources in Differential-GPSIonosphere Troposphere Error in Satellite Orbit

12. 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

13. Tropospheric Scale Factor Convergence on the Network Stations Minutes Scale factor offset

14. Improvement due to Tropospheric Scaling in the Bysat Network

15. 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

16. Average yearly number of sun spots 0 50 100 150 200 19601970198019902000 RZ 25 20 15 10 5 0 19701960198019902000 Year Ionospheric error in GPS L1 Error [m] Solar Cycle and Ionosphere

17. Ionospheric Maximum in 2000/2001 19951995,519961996,519971997,5199919981999,51998,520002000,5 5 10 15 20 25 30 35 Time (Years) Mean TEC (TECU) CODE Ionospheric model Station Zimmerwald, CH CODE Ionospheric model Station Zimmerwald, CH

18. 0.06 0.05 0.04 0.03 0.02 0.01 0.00 -0.01 -0.02 -0.03 -0.04 -0.05 -0.06 13:0013:1013:2013:3013:4013:5014:00 Local Time Error in Meter Differential Ionosphere Dec. 1998 on 70 km Baseline

19. Local Time Error in Meter 13:0013:1013:2013:3013:4013:5014:00 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

20. Local Time Error in Meter 13:0013:1013:2013:3013:4013:5014:00 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

21. 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

22. Integrity Monitoring  Outlier detection in pseudo-ranges u Continuous navigation solution for all stations u Continuous DGPS solution for all stations  In case of outliers the epoch will not be used

23. Network Processes  Geometric correction  Correction for tropospheric errors  Correction for ionospheric errors  Correction for multi-path  Ambiguity resolution  Consistency check

24. 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 u geometrical part (troposphere and ephemeris), typical < 2 ppm u ionospheric part, typical < 15 ppm  Computation of corrections performed once per second

25. 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

26. Data Communication

27. Software Structure

28. 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

29. Performance Analysis in the Bysat Network Höhenkirchen Mainburg 70 km Augsburg Mühldorf Rover Neufahrn - Data of February 2000 - 90 hours day/night - Rover in Neufahrn, 32 km from Höhenkirchen from Höhenkirchen

30. 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

31. Improvement in Time to Fix by using VRS

32. 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

33. Error in North – 32 km Baseline Confidence Level 90 %: < 13 mm 99 %: < 26 mm Confidence Level 90 %: < 13 mm 99 %: < 26 mm

34. Error in East – 32 km Baseline Confidence Level 90 %: < 9 mm 99 %: < 21 mm Confidence Level 90 %: < 9 mm 99 %: < 21 mm

35. Error in Height – 32 km Baseline Confidence Level 90 %: < 25 mm 99 %: < 49 mm Confidence Level 90 %: < 25 mm 99 %: < 49 mm

36. RTK Initialisation – 32 km Baseline Performance 50 %: < 40 sec 90 %: < 80 sec average: 58 sec Performance 50 %: < 40 sec 90 %: < 80 sec average: 58 sec

37. Bysat Network – 32 km : 11AM – 4PM 90 % < 17 mm 99 % < 37 mm 90 % < 17 mm 99 % < 37 mm Average 60 seconds Average

38. Conclusion  GPS-Network successfully creates improved VRS RTCM corrections in real-time  VRS reduces systematic errors substantially, but cannot eliminate them completely  VRS allows to do RTK positioning at distances a standard RTK system never will reach  Virtual Reference Stations improve: u Accuracy u Productivity via shorter Time to Fix u Reliability