Relative GPS Carrier-Phase Positioning Using Particle Filters with Position Samples

In this paper, the problem of precise relative positioning using GPS (Global Positioning System) Carrier-Phase (CP) information is addressed. The unknown cycle ambiguity between GPS satellites and antennas at the moment of receiving the CP signal should be resolved for precise navigation. The sequential Monte Carlo filter approach, called particle filter (PF), is applied to the relative positioning problem which includes the ambiguity resolution problem for the CP nonlinear observation and dynamic equations. The proposed algorithm of GPS CP navigation is based on two main factors. First, even though most existing GPS CP navigation algorithms focus on obtaining the correct integer value among the integer candidates, we directly sample from the three dimensional position space and construct integers consistent with the PE This allows the PF position estimates to be insensitive to changes of GPS satellites and cycle-slips. Second, the potential large number of samples in position space is handled with the resampling technique in the sequential particle filters. The experimental results show the performance and the advantages of the proposed approach compared to the existing methods.