Abstract:

An improved filter algorithm combined strong tracking filter (STF) with unscented Kalman filter (UKF) is proposed to enhance poor performance of extended Kalman filter (EKF) and UKF in online adaptive adjustment ability and estimation accuracy when systems are abnormal. The process of solving Jacobi matrix in observer equation is avoided by deeming partial state information as indirect measurement and adjusting the measurement noise variance matrix online, which makes the filter design more simplified. The algorithm is applied to spacecraft autonomous navigation and simulation results show that when abrupt or slow abnormalities of systems occur, the proposed algorithm can detect abnormalities rapidly, and guarantee high estimation accuracy and reliability of the system at the same time.