Reliability is an essential factor for GPS navigation system. Therefore, an integrity monitoring is considered one of the most important parts for a navigation system. GPS receiver autonomous integrity monitoring (RAIM) technique can detect and isolate fault satellite. Based on particle filter, a novel RAIM method was proposed to detect two-satellite faults of the GPS signal by using hierarchical particle filter based probability test. The particle filter is popular filtering methods to estimate states of a general dynamic system. It can deal with any system nonlinear and any noise distributions. Because GNSS measurement noise does not follow the Gaussian distribution perfectly, the particle filter can estimate the posterior distribution more accurately. In order to detect fault, the consistency test statistics is established through cumulative log-likelihood ratio (LLR) between the main and auxiliary particle filters (PFs).Specifically, an approach combining PF with the hierarchical filter is used in the process of two-satellite faults. Through GPS real measurement and the application of the RAIM method, the performance of the proposed GPS twosatellite faults detection algorithm was illustrated. Some simulation and experiment results are given to evaluate integrity monitoring performance of the algorithm. Validated by the real experimental data, the results show that the proposed algorithm can successfully detect and isolate the faulty satellite in the case of non-Gaussian measurement noise.
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Wang et al. (2016) studied this question.
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