Unmasking Bayesian RAIM Algorithm for Identifying Simultaneous Two-Faulty Satellites

摘要

For the problem of identifying simultaneous two-faulty satellites in global navigation satellite systems (GNSS), an unmasking Bayesian Receiver autonomous integrity monitoring (RAIM) algorithm is proposed. In order to prevent the interaction between the two faults, the posterior distribution of observation error is obtained and the posterior probabilities of the events related to the observation errors of two satellites are calculated based on Bayes statistical theory, The complex posterior probability calculation formula is transformed into sample average by using Monte Carlo method, which meets the real-time requirements of identifying method. The simulation results based on the precise ephemeris products provided by iGMAS show that the proposed algorithm can identify two satellite faults quickly and accurately, and improve the accuracy of navigation and positioning to a certain extent. Compared with the previous RANCO method, it shows that the method is feasible, not only can effectively identify the fault, but also can effectively prevent the interaction between the two faults.