首页|A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system
A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system
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NETL
NSTL
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In this study,the problem of measuring noise pollu-tion distribution by the intertial-based integrated navigation sys-tem is effectively suppressed.Based on nonlinear inertial naviga-tion error modeling,a nested dual Kalman filter framework struc-ture is developed.It consists of unscented Kalman filter(UKF)master filter and Kalman filter slave filter.This method uses non-linear UKF for integrated navigation state estimation.At the same time,the exact noise measurement covariance is esti-mated by the Kalman filter dependency filter.The algorithm based on dual adaptive UKF(Dual-AUKF)has high accuracy and robustness,especially in the case of measurement information interference.Finally,vehicle-mounted and ship-mounted inte-grated navigation tests are conducted.Compared with tradi-tional UKF and the Sage-Husa adaptive UKF(SH-AUKF),this method has comparable filtering accuracy and better filtering stability.The effectiveness of the proposed algorithm is verified.
NETL
NSTL
万方数据
