Research on Exact Thresholds for ARAIM MHSS Fault Monitoring

Abstract

Multiple Hypothesis Solution Separation (MHSS) is the baseline algorithm for Advanced Receiver Autonomous Integrity Monitoring (ARAIM), and it detects faults by comparing the test statistic with a threshold. However, the cuboid threshold structure of the MHSS fault monitoring baseline algorithm lacks omnidirectionality, which leads to low conformity between the threshold and the spatial distribution of the test statistic and to low fault monitoring accuracy. To resolve these problems, we analyzed the distribution of a test statistic for single-, double-, and triple-fault hypotheses. By extracting the eigenvectors and eigenvalues of the solution separating variance, we designed an omnidirectional threshold structure. The simulation verifies the effectiveness of the fault detection method by detecting faults from noise. The results show that the proposed method is more exact, stable, and applicable than the MHSS fault detection baseline.