基于双旋迫击炮弹平台的改进型Sage-Husa自适应滤波滚转角测量算法

Traditional extended Kalman filter (EKF) algorithm is unable to eliminate the bigger measured roll angle error caused by irresistible measuring noise. A roll angle estimation algorithm with improved Sage-Husa adaptive Kalman filtering (SHAKF) based on dual-spin mortar shell is proposed, in which the measured rotation speed of gyro is used as compensation for system noise. Compared with traditional EKF algorithm, the proposed algorithm is used to reduce the measuring error of roll angle significantly, and improve the adaptivity of filter to the innovation changing of roll angles in the upward and downward legs of ballistic trajectory. The new proposed algorithm is verified by in-lab testing with MEMS three-axis turntable. The research results indicate that the mean value and standard deviation of measuring errors are 0.26 degs and 0.35 degs, respectively, in simulating verification, and the in-lab testing results show that the estimation error is always less than 4.2 degs in dynamic range changing from 30 r/s to 1 r/s.