Research on GPS Receiver Autonomous Integrity Monitoring Based on Auxiliary Particle Filter

Abstract

AbstractUtilizing the great advantages of the particle filter in processing nonlinear system with non-Gaussian noise, a new approach combining auxiliary particle filter (PF) with log-likelihood ratio (LLR) method is proposed for GPS receiver autonomous integrity monitoring (RAIM). Processing respectively all the measurements and partial measurements by particle filter algorithm, the fault satellite can be detected through establishing test statistics based on the log-likelihood ratio method. A theoretical analysis is implemented on the probability distribution of the log-likelihood ratio test statistic, and the detection threshold can be set according to the probability of false alarm. The satellite fault can be detected by comparing the system each epoch cumulative log-likelihood ratio with the detection threshold and can be isolated by the maximum likelihood criterion. Validated by the measured real data from GPS receiver are deliberately contaminated with the bias and ramp terms error, the results show that the proposed auxiliary PF accurately estimated the state of GPS receiver in the case of non-Gaussian measurement noise, successfully detected and isolated the faulty satellite by establishing log-likelihood ratio statistic for consistency test, verified the feasibility and effectiveness of applying the auxiliary PF in the GPS receiver autonomous integrity monitoring.KeywordsGlobal positioning system (GPS)Receiver autonomous integrity monitoring (RAIM)Auxiliary particle filterFault detection