Single-based RTK positioning: in demand for a longer inter-receiver distance, and yet for the same performance as with a short baseline Key issue: ability.

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Single-based RTK positioning: in demand for a longer inter-receiver distance, and yet for the same performance as with a short baseline Key issue: ability to resolve long-range carrier phase ambiguity in (near) real-time Problem: long-range ambiguity resolution is complicated due to the presence of distant-dependent errors i.e; ionosphere effect and troposphere delay (and orbit error) Ionospheric Effect Can be effectively cancelled over a short baseline 1-50ppm depending on solar activity and geomagnetic location Can be eliminated by a double frequency receiver (Iono-free combination) Tropospheric Delay Apply a priori or physical models (Saastamoinen, Hopfield, etc) Can model the dry component effectively but not the wet comp. 1-3ppm depending on geographic location and satellites’ elevation Common approach : estimation of troposphere scale factor, or stochastic estimation (not suitable for RTK mode). Orbit Error Broadcast ephemeris – accuracy < 200cm, real-time IGS Ultra Rapid Orbit – accuracy < 10cm, real-time Not critical to the baseline computation Approach: use a local GPS network to better estimate and model distance-dependent errors Dynamic Planet 2005 August , Cairns Australia dUp dNdE Modelling of Dispersive and Non-dispersive Effects on Network-Based Positioning Tajul A. Musa, Samsung Lim, and Chris Rizos School of Surveying and Spatial Information Systems UNSW, Sydney, NSW 2052, Australia Advantages Advanced network error modeling Users are in control of correction application Extra processing strategy for users Network Correction Generation Geometry-Free (GF) combination for dispersive term Ionosphere-Free (IF) combination for non-dispersive term Frequent update of dispersive-term modelling Less frequent modelling for non-dispersive term – smoothing technique can be applied Network User Processing (strategy) Improved IF with non-dispersive correction is useful for narrow- lane ambiguity resolution Combined dispersive and non-dispersive correction improves a user’s position computation Centre User Stn Ref. Stn Master Stn Raw Net Corr Master-to-Reference Process Generating Network Correction User Process Residual interpolation (2D,3D) Correction separation Improv. measurements Improv. ambiguity estimation Improv. position accuracy Network ambiguity Network residuals Network Approach Why separate the network correction? Dispersive term has high variation of ionosphere effect Non-Dispersive term has small/slow variation of troposphere effect (and orbit error) Overview: Single-Based vs Network-Based RTK Test Area 2 : SIMRSN, SINGAPORE (low latitude) Test Area 1 : SYDNET, AUSTRALIA (mid-latitude) Lat : 1  15’ - 1  30’ N Long: 103  40’  59 E SINGAPORE South East Asia LOYA SEMB NTU0 KEPC NYPC 14km Lat : 33  36’ - 34  08’ S Long: 150  34’  12’ E 43km WFAL CWAN SPWD VILL UNSW Cut-off Elev. Case Init.Single-BasedNetwork-Based Correct % Reject % Wrong % Correct % Reject % Wrong % 10    Cut- off Elev. Case Init.Single-BasedNetwork-Based Correct % Reject % Wrong % Correct % Reject % Wrong % 10    Instantaneous Ambiguity Resolution & Validation SYDNET (SPWD-VILL) SIMRSN (LOYA-NYPC) SYDNET (F-Ratio) 10  15  20  SIMRSN (F-Ratio) 10  15  20  CONCLUDING REMARKS Separation of the network correction allows further error modelling and user processing strategy Proposed strategy performs reasonably well with the two local GPS networks (SYDNET and SIMRSN), and improves ambiguity resolution process and therefore user position computation Net. User Position Accuracy dUp dNdE Stn. VILL Stn. NYPC CorrMeanDeviation dEDNdUpdEdNdUp w/o with CorrMeanDeviation DEDNdUpdEDNdUp w/o with