Integrity monitoring with MAIME upon integrated GNSS/SINS for SGEs

An integration of Global Navigation Satellite System (GNSS) and Strapdown Inertial Navigation System (SINS) have revolutionized navigation industries significantly. However, the integrated GNSS/SINS system has the highest potential for detecting slowly growing errors (SGEs), which is the most difficult to detect in navigation field at the same time. A novel methodology has been developed for failure identification upon GNSS/SINS for SGEs. It is applicable to carrying on the integrated navigation Kalman filter and new dimension measurements, which makes full use of the historical epochs for multi-step extrapolation. Moreover, we manage to provide more effective test statistics compared with widely used Autonomous Integrity Monitoring by Extrapolation Method (AIME), which is called Enhanced Autonomous Integrity Monitoring by Extrapolation Method (EAIME). Correspondingly, theoretical thresholds of different false alarm are put forward. Making full use of the numerical modeling and test statistic approach, simulation results show that the statistics of EAIME could achieve better performance compared with classic AIME.