Fault Diagnosis Algorithm for Redundant Dual-Axis RINSs Based on Geometric Constraint Observation

Dual-axis rotational inertial navigation systems (DRINSs) have been widely used in marine navigation due to their high accuracy. However, the long-term operation of a DRINS over weeks poses a significant challenge to its reliability. In order to address the fault diagnosis challenges faced by DRINSs on long-endurance vessels in global navigation satellite system (GNSS)-denied environments, this paper proposes a fault diagnosis algorithm for redundant DRINSs based on geometric constraint observation. The mechanization of dual DRINSs is implemented using a globally referenced framework. A residual-normalized strong tracking filter based on geometric constraint observation is employed to estimate the fault states of the dual DRINSs. A highly robust fault diagnosis method is proposed to detect and diagnose faults in the inertial devices of dual DRINSs. The experimental results show that the proposed algorithm exhibits excellent performance with a diagnostic accuracy of 98.67% and low diagnostic delay.