Multi-Fault Detection and Isolation for Redundant Strapdown Inertial Navigation System

Jianhua Cheng, Xiangyu Sun, Daidai Chen, Chun Cheng, Hongjie Mou, Ping Liu

Peer Reviewed

Abstract: Traditional generalized likelihood test method can detect faults while can not isolate multiple faults in redundant strapdown inertial navigation system. In this paper, a multi-faults detection and isolation method based on generalized likelihood test and linear prediction approach is proposed. A generalized likelihood test method is used to detect the fault of the system, and the linear prediction method is used to estimate the values of inertial sensors. The faulty inertial sensors can be isolated through comparing the estimated values with measurements of inertial sensors, and the faulty information is recorded for system reconstruction. Through simulation and experiment, it is proved that new method can accurately detect and isolate multiple faults and thus guarantee the reliability of strapdown inertial navigation system.
Published in: 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 1562 - 1569
Cite this article: Cheng, Jianhua, Sun, Xiangyu, Chen, Daidai, Cheng, Chun, Mou, Hongjie, Liu, Ping, "Multi-Fault Detection and Isolation for Redundant Strapdown Inertial Navigation System," 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, April 2018, pp. 1562-1569.
Full Paper: ION Members/Non-Members: 1 Download Credit
Sign In