Research On Data Processing Algorithm In GPS Receiver Positioning Reliability

With the development of Global Positioning Systems (GPS) and the increasingrequirements of users for satellite navigation and positioning performance, the availability andreliability of satellite navigation has been increasingly important seriously. Reliability is anessential factor in a navigation system. Due to system faults, biased information requiresintegrity monitoring for performance support, therefore, a receiver autonomous integritymonitoring (RAIM) system is considered as one of the most important parts in an avionicnavigation system.In this paper, for the fault monitoring capability declining problem of the traditional GPSsatellite fault detection algorithm under small fault amplitude, a new GPS satellite faultdetection algorithm based on wavelet transform is proposed. Using wavelet analysis forperforming data processing on the pseudo-range observation value and the positioninformation, the signal mutation point is identified by singularity changes on the differentscales, and then the satellite fault could be detected. The wavelet analysis method can welldetect smaller mutations in a sequence of parameters, improve the accuracy of fault detection,and verify the feasibility and effectiveness of applying the wavelet analysis method in theGPS satellite fault detection.According to the condition that RAIM technology requires redundant observationinformation, the RAIM availability of the selected satellites needs to be analyzed beforeapplying RAIM algorithm to detect and isolate fault satellites. Based on the GPS, research theHorizontal Positioning Level, and describe the principle of fault detection and availability ofthe RAIM algorithm. Combined with navigation performance requirements in aviation flightapplication phase, simulate the factors affecting the availability of RAIM. Research resultsprovide the usability basis for fault satellite detection and isolation by adopting the RAIMalgorithm.This paper applies a GPS integrity monitoring method of combining particle filter andlikelihood ratio test to fault detection and isolation. The measured data from GPS areartificially added with two different types of faults, namely the bias and ramp terms. Based onthe simulation result, the proposed approach can detect the GPS measurement fault,particularly shows outstanding detection performance when the fault is obvious. In order to recognize GPS double faults quickly and efficiently and improve the reliability of the satellitenavigation system, the particle filter algorithm combines with the level filter algorithm to beused for RAIM. This paper establishes the mathematical model, so as to detect and isolatedouble-fault satellites by checking the cumulative log-likelihood ratio of system state withdetection threshold. Validated by experimental data, the results show that the proposed FDIalgorithm can successfully detect and isolate the double-fault satellites in the case ofnon-Gaussian measurement noise, thus verifying the feasibility and effectiveness of applyingthe particle filter and the level filter in the RAIM.