Particle filter algorithm has a great advantage in processing nonlinear and non-Gaussian noise problems, so an approach combining the particle filter algorithm with the log-likelihood ratio (LLR) is presented for GPS receiver autonomous integrity monitoring (RAIM). The state estimate is calculated precisely by the particle filter algorithm and LLR is used as a consistency test statistic to achieve the fault detection. By setting up the total and partial cumulative LLRs, the satellite fault is detected by checking the cumulative LLR of system state with detection threshold. The mathematical model of the algorithm is established. Meanwhile, the algorithm flow is described. Based on the real GPS data, the RAIM algorithm is tested. Experimental result demonstrates that the particle filter algorithm can accurately estimate the state of GPS receiver under conditions of non-Gaussian measurement noise, and LLR as the statistic of consistency test can effectively detect and isolate fault satellite, thus validating the feasibility and validity of particle filter and likelihood ratio methods for RAIM.