A Self-Alignment Method for HRG-SINS Based on Novel Self-Calibration Method and Error Model for Underwater Vehicle

Strapdown Inertial Navigation Systems (SINS) provide autonomous navigation for underwater vehicles using Inertial Measurement Unit (IMU) data. SINS can achieve initial alignment through self-calibration technology before entering the navigation stage. However, gyroscope biases and scale factor errors degrade alignment accuracy. Hemispherical Resonator Gyroscope (HRG) is a new type of high-precision gyroscope. When operated in Force-to-Rebalance (FTR) mode, it exhibits low-noise characteristics and supports mode reversal for self-calibration of bias and scale factor, thus enhancing SINS alignment precision. When a certain HRG performs self-calibration, it causes output interruption angular velocity. At this time, other HRGs need to provide angular velocity as the reference and maintain the regular operation of SINS. Therefore, a mode reversal sequence is designed based on the FTR-mode HRG and the 4-HRG-SINS structure. The error equations for bias and scale factor of 4-HRG-SINS were established, and the optimal estimation of bias and scale factor errors was achieved through the Kalman filter (KF). Then, coarse alignment is performed to obtain rough attitude and latitude. Finally, integrating the results of self-calibration and coarse alignment with the novel HRG-SINS error models, the fine alignment scheme is developed using a backtracking framework. Finally, both simulations and semi-physical simulations validate the algorithm’s effectiveness.