Multiple Iterative Kalman Filter SINS Initial Alignment Algorithm

Abstract

Initial alignment is the pre-step of the SINS navigation solution. High-precision initial alignment technology is an important guarantee for SINS's long-time, long-distance, and high-precision navigation and positioning. Kalman filter, as an important method of the initial fine alignment process, has been widely used in engineering practice. This paper is based on the indirect Kalman filter closed-loop algorithm, in order to make full use of the observation information, multiple iterative operation is performed on the state vector obtained from the Kalman filter feedback correction, and a more accurate state vector prediction result is obtained to reduce the linearization error and then the filter accuracy is improved. The final simulation results show that the proposed method can significantly improve the yaw alignment accuracy under the condition of different small initial yaw misalignment angles, which prove the effectiveness of the proposed algorithm.