A Self-Calibration Method for the Installation Errors of Rotation Axes Based on the Asynchronous Rotation of Rotational Inertial Navigation Systems

The attitude accuracy of the rotational inertial navigation system (RINS) is affected by the oscillatory attitude error caused by the installation error of the rotation axes. Data on the specific force, gyro measurement, attitude, or velocity errors are necessary to estimate the installation error. However, these errors are difficult to obtain and even unavailable in autonomous navigation. As the configuration consisting of two RINSs has been installed in the same vessel, we propose a self-calibration method to address the installation error solely using the attitude difference of two RINSs. We then constructed the Kalman filter based on the attitude difference model of two RINSs. The asynchronous time of the rotation sequence of two RINSs is optimized to improve the observability degree of the Kalman model. The proposed algorithm is examined by undertaking a test using two RINSs. Results indicate that the estimation accuracy of the installation error is at 6 arcsec level. The oscillatory attitude errors of RINS 1 are reduced from 305 to 6 arcsec, and those of RINS 2 are decreased from 131 to 6 arcsec after 350 s. The test results prove the effectiveness of the proposed installation error calibration method.