Initial Alignment of Large Azimuth Misalignment Angle in SINS based on Reduced Multiple Fading Factors Strong Tracking CKF

Aiming at the problem that Cubature Kalman Filter(CKF) has low accuracy and robustness under the condition of strapdown inertial navigation system(SINS) initial alignment due to model error and external disturbance, Reduced Multiple Strong Tracking Cubature Kalman Filter(RMSTCKF) is proposed, and the algorithm flow and sub-optimal solution of multiple fading factor are derived. Multiple fading factor can improve tracking ability under each state according to the degree of uncertainty of different states, having stronger adaptability and robustness. Applying RMSTCKF to large azimuth misalignment angle error function described by Euler platform error angle(EPEA), carrying out the simulation under two different conditions, namely noise mismatch and the base is disturbed, and making contrast between RSTCKF and RCKF, the simulation results show that the filter accuracy and convergence rate of RMSTCK when system noise mismatches with true noise are obviously better than RSTCKF and RCKF, having better practical value in engineering