Computation and quality control of differential GPS corrections

Abstract

The DGPS technique can considerably improve the accuracy of stand-alone GPS positioning, but the improvement depends on the distance between the user and the reference station (spatial correlation), the latency of differential corrections (temporal correlation), and the quality of differential corrections. Therefore, how to correctly generate differential corrections as well as their precision is one of the keys to the DGPS positioning technique. This paper presents a new algorithm for generating differential GPS corrections. This algorithm directly uses code and carrier observations in the measurement model of a Kalman filter, so that it is possible to use a simple stochastic observation model and to use the standard algorithm of the Kalman filter. The algorithm accounts for biases like multipath errors and instrumental delays in code observations and it clearly shows how differential corrections are differently affected by code biases when dual or single frequency data are used. In addition, the algorithm can be integrated with a recursive quality control procedure. As a consequence, the quality of differential corrections can be guaranteed with certain probability.