Fast Self-Alignment and Self-Calibration Method for Rotational Inertial Navigation System Based on Environment Function Matrix

This article proposed a stationary base alignment and calibration method based on optimization to solve the problem of fast in-field calibration before using a rotational inertial navigation system (RINS). This method only needs to calculate the numerical integral and least square and does not need the prior distribution of error coefficients and noise parameters. It avoids the convergence problem of the filter-based method and has good robustness and accuracy. At the same time, the proposed method is used for fine alignment and fine calibration, which changes the previous situation that the optimization-based alignment (OBA) and calibration are mainly used for coarse alignment and coarse calibration. In order to achieve this, the environment function matrix (CFM) theory is introduced and thus turns alignment and calibration into a least squares problem. Simulation shows that the method has higher accuracy than the filter-based method. In rotation modulation navigation experiments, the navigation position error of the proposed method is about 13.7%–29.1% of the traditional method and the velocity error is only about 17.2%–17.3% of the traditional method, proving that the proposed method can significantly improve the navigation accuracy of the RINS.