Research on improved fine alignment methods

Abstract

Based on the hypothesis of small values of misalignment angles, compass alignment and linear Kalman alignment are common fine alignment methods. The algorithm of compass alignment has good robustness, but the convergence efficiency and accuracy of alignment are contradictory, which is necessary to set appropriate control parameters to reconcile. Because Kalman alignment method is based on a deterministic filtering model, the algorithm is relatively stable, but the drift of IMU (Inertial Measurement Unit) will cause the drift of the errors of misalignment angles. In order to take into account the effects of both long and short damping periods on compass alignment, the exponential finite time-varying damping period is used to improve the convergence efficiency of azimuth alignment. In order to solve the divergence of horizontal misalignment angles of Kalman precise alignment algorithm, a realtime correction algorithm of attitude matrix with full feedback of misalignment angle estimations is introduced. The simulation and turntable experiments verify the effectiveness of the improved methods.