Performance improvement for GPS single frequency kinematic relative positioning under poor satellite visibility

Reliable ambiguity resolution in difficult environments such as during setting/rising events of satellites or during limited satellite visibility is a significant challenge for GPS single frequency kinematic relative positioning. Here, a recursive estimation method combining both code and carrier phase measurements was developed that can tolerate recurrent satellite setting/rising and accelerate initialization in motion. We propose an ambiguity dimension expansion method by utilizing the partial ambiguity relevance of previous and current observations. In essence, this method attempts to integrate all useful information into the recursive estimation equation and performs a better least squares adjustment. Using this method, the success rate of the extended ambiguity estimation is independent of the satellite setting and shows robust performance despite poor satellite visibility. Our model allows integration of other useful information into the recursive process. Actual experiments in urban environments demonstrate that the proposed algorithm can improve the reliability and availability of relative positioning.