A Fault-Tolerant H-Infinity Federated Filter Algorithm for Integrated Navigation Systems

This paper presents a fault-tolerant H-infinity federated filter (FTHIFF) algorithm based on strapdown inertial navigation system (SINS), doppler velocity log (DVL), celestial navigation system (CNS) and global navigation satellite system (GNSS). In order to correct the divergence error of SINS, the method introduces the attitude information of CNS, the velocity information of DVL, and the position information of GNSS. The classic federated filter's Kalman filter is upgraded to the H-infinity unscented Kalman filter (HIUKF) in order to increase the navigation system's robustness and accuracy. A decreasing sequential probability ratio test (DSPRT) is presented as a defect detection, isolation, and recovery procedure to fix the error in the local filter and recover the data. Simultaneously, an information sharing algorithm (ISA) based on DSPRT findings and the difference between actual and expected observations is created. This ISA may be used to evaluate the effectiveness of each local filter. The experimental results demonstrate that the presented integrated navigation and positioning algorithm is capable of increasing positioning accuracy while maintaining system stability in the event of sensor failure.