Online self-calibration research of single-axis rotational inertial navigation system

Abstract

Rotary modulation can greatly improve the inertial navigation system (INS) performance. Based on the single-axis rotational inertial navigation system (RINS) with fiber optic gyroscopes (FOGs), this study analyzed the key errors which would affect the navigation accuracy of single-axis RINS and proposed a novel calibration method. The method uses horizontal accelerometer outputs, horizontal attitude errors and heading angle as the measurements of Kalman filter to achieve online self-calibration based on the designed rotation scheme. Through online self-calibration, the non-repeatable errors of each start in system could be estimated and compensated, and then the navigation accuracy of system can be significantly improved. Compared with the traditional methods, using the proposed method can get higher observability degrees of the key errors in system and shorten the calibration time. Simulation and experimental results show that the entire online self-calibration process can be completed within 48 min on stationary base and after online self-calibration, the short-term attitudes vibration is suppressed greatly, and the RINS position accuracy could improve about 50% in long-term navigation applications.