Weighted Least Squared Approach to Fault Detection and Isolation for GPS Integrity Monitoring
Reliability of a global navigation satellite system is one of great importance for global navigation purposes. Therefore, an integrity monitoring system is an inseparable part of aviation navigation system. Failures or faults due to malfunctions in the systems should be detected to keep the integrity of the system intact. In order to solve the problem that least squares method detects and isolates a satellite fault for GPS integrity monitoring, in this paper, a weighted least squares algorithm is proposed for satellite fault detection and isolation. The algorithm adopts the diagonal elements of the covariance matrix of GPS measurement equation as the weighted factor. Firstly, the weighted least squares approach for satellite fault detection establishes the test statistic by the sum of the squares of the pseudo-range residuals of each satellite for GPS. Then, the detection threshold is obtained by the false alarm rate of the fault detection, probability density function and visiable satellite number.The effectiveness of the proposed approach is illustrated in a problem of GPS (Global Positioning System) autonomous integrity monitoring system. Through the real raw measured GPS data，based on least squares RAIM method and the weighted least squares RAIM approach, the performance of the two algorithms is compared. The results show that the proposed RAIM approach is superior to the least squares RAIM algorithm in the sensitivity of fault detection and fault isolation performance for GPS integrity monitoring.
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