A New Stochastic Modelling Procedure for Precise Static GPS Positioning

Carrier phase measurements are used for all high accuracy static GPS positioning applications. It is well known that there are two important aspects to the optimal processing of GPS measurements: the definition of the functional model, and the definition of the associated stochastic model. In most cases the functional model is sufficiently well known, while the definition of the stochastic model still remains a challenging research topic. In this paper, a new stochastic modelling procedure is developed and employed in the processing of GPS data for static positioning applications. This procedure takes into account the heteroscedastic, spaceand time-correlated error structure of the GPS measurements. To demonstrate its performance, both simulated and real data sets for short to medium length baselines have been analysed. The results indicate that the accuracy of GPS positioning results can be improved to the millimetre level.