Fault diagnosis algorithm for redundant dual-axis RINSs based on geometric constraint observation

Dual-axis rotational inertial navigation system (DRINS) has been widely used in marine navigation due to its high accuracy. However, the long-term operation of DRINS for tens of days poses a significant challenge to its reliability. In order to address the fault diagnosis challenges faced by DRINS 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 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.