Fault Diagnosis and Initial Alignment of Redundant SINS Under Large Misalignment Angle

This article investigates an integrated approach of fault diagnosis and initial alignment of redundant strapdown inertial navigation systems (SINSs) under large misalignment angles. A redundant configuration of four hemispherical resonator gyroscopes (HRGs) and four accelerometers is designed. The parity vector method combined with generalized likelihood ratio test is developed for reliable detection and identification of HRG bias faults. For initial alignment, an analytic coarse alignment provides an initial attitude estimate, which is followed by a precise alignment phase using an unscented Kalman filter (UKF). The UKF is specifically designed to handle the nonlinear error model associated with large yaw misalignment angles. Experimental results demonstrate that the proposed fault diagnosis method effectively identifies HRG faults. Furthermore, comparative studies show that while the UKF and extended Kalman filter yield similar performance for small misalignment angles, the UKF achieves significantly superior alignment accuracy, especially under large yaw misalignment angle. This integrated approach enhances system reliability and navigation precision, which achieves a 100% detection rate for the tested bias faults and reduces the yaw error from$20^{\circ }$to below$0.35^{\circ }$.