Fault Identification Method of GNSS/INS Integrated Navigation System Based on the Fusion of Chi-Square Test and Multiple Solution Separation Algorithm

In view of the problem that the fault identification algorithm of Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated navigation is difficult to balance the complexity and performance, this paper proposes an efficient fault identification method. Firstly, the propagation process of GNSS faults in Kalman filtering is analyzed, and the chi-square and multiple solution separation test statistics considering fault propagation are designed. Secondly, a fusion algorithm of chi-square and multiple solution separation using multiple solution separation algorithm on demand is proposed, only when the chi-square test statistic is greater than the threshold, the multiple solution separation algorithm is activated for fault identification, and use the chi-square test to replace the corresponding steps in the multiple solution separation algorithm to complete the exclusion test to reduce the number of subsets. Finally, aiming at the threshold design for the above fault identification method, the total continuity risk and integrity risk are allocated according to the integrated navigation mechanism, and the calculation and selection of the algorithm threshold are completed by using the allocation results. The simulation results show that the fusion of the two algorithms can complement each other’s advantages, identify faulty satellites accurately and efficiently, record the capture time of the fault, and complete fault exclusion. At the same time, the comparison with the (m − 1) method, multiple solution separation algorithm, and discarding all observations of the faulty sensor, etc., proves that this method achieves a good balance between algorithm performance and complexity.