Abstract: An Adaptive Square Root Central Difference Kalman Filter (ASRCDKF) algorithm is proposed, which is used in the initial alignment of Strapdown Inertial Navigation System (SINS) with large azimuth misalignment angle. The basis of this algorithm is central difference transform, and square root of covariance is used instead of covariance in recursive calculation based on the theory that square root filter can overcome filter divergence. In addition, adaptive estimation principle is introduced in this algorithm. The ASRCDKF algorithm not only overcomes the shortcomings that extended Kalman filter can generate linear error and it needs to calculate Jacobian matrix, but also reduces calculation amount to ensure numerical stability. Furthermore, this algorithm solves the problem that traditional filter algorithm relies on a prior knowledge of the system dynamic model and noise statistic characteristics. Simulation results fully verify the effectiveness and superiority of the ASRCDKF algorithm in SINS initial alignment with large azimuth misalignment angle.

Key words: information processing, large azimuth misalignment angle, strapdown inertial navigation system (SINS), initial alignment