Thursday 25 August 2005

G1

PTH0006
Modifying the stochastical model to mitigate GPS systematic errors in relative positioning
Monico, João Francisco Galera¹, Alves, Daniele Barroca M¹
1 Cartography Department - FCT/UNESP, Brazil
2 Graduate Program on Cartographic Science - FCT/UNESP, Brazil
Author email: galera@prudente.unesp.br
The GPS observables are subject to errors. Among them, the systematic ones have great impact, because they degrade the accuracy of the accomplished positioning. These errors are those related, mainly, to GPS satellites orbits, multipath and atmospheric refraction. Recently, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique (PLS) (ALVES, ION GNSSS 2004). In this method, the errors are modeled as functions which vary smoothly in time. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method (CLS). Therefore, the solution requests a shorter data collection interval, minimizing costs. Aiming to analyze the method performance, two experiments were carried out using data from single frequency receivers. The first one was accomplished with a short baseline, where the main error was due to multipath. In the second one, a baseline of 102 km was used. In this case, the predominant errors were due to the ionosphere and troposphere refraction. In the first experiment, using 5 minutes of data collection, the largest coordinates discrepancies in relation to the ground truth reached 1.6 cm and 3.3 cm in h coordinate for PLS and the CLS, respectively. In the second one, also using 5 minutes of data, the discrepancies were 27 cm in h for the PLS and 175 cm in h for the CLS. In these tests, it was also possible to verify a considerable improvement in the ambiguities resolution using the PLS in relation to the CLS, with a reduced data collection time interval. Besides, in this paper, it will be shown that changing the stochastical model, incorporating the errors functions, the results obtained are similar to those in which the functional model is changed (BLEWIT, 1996, GPS for Geodesy).

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