Particle Filtering Approach To Fault Detection and Isolation for GPS Integrity Monitoring

Abstract

Reliability of a navigation system is one of great importance for 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 and repaired to keep the integrity of the system intact. In this paper, we present a method based on particle filtering for detecting failures which affect only subsets of system measurement. In addition to a main particle filter, which processes all the measurements to give the optimal state estimate, a bank of auxiliary particle filters is also used, which process subsets of the measurements to provide the state estimates which serve as failure detection references. After the statistical property of the state estimate of the main particle filter and those of the auxiliaries is derived, failure detection is undertaken by checking the consistency between the state estimate of the main particle filter and those of the auxiliaries by means of the likelihood ratio (LR) test. The effectiveness of the proposed approach is illustrated in a problem of GPS (Global Positioning System) autonomous integrity monitoring system.