Spacecraft autonomous navigation based on SSUKF algorithm

An improved unscented Kalman filter (UKF) algorithm based on spherical simplex unscented transformation (SSUT) was presented to satisfy the stability, precision and real time requirements of spacecraft autonomous navigation. The SSUT reduces the sigma points for the unscented transformation. Compared with the traditional UKF, the computational efficiency of spherical simplex unscented Kalman filter (SSUKF) was improved, without sacrificing the estimation precision. According to the similar computation process of UKF and extended Kalman filter (EKF), the combined Kalman filter based on SSUKF and EKF was designed. This algorithm can switch adaptively between the SSUKF and EKF through a mode switching function which is the criterion of estimation errors. It solves both the inefficiency problem of UKF and the instability problem of EKF. Simulation results show that the combined Kalman filter integrates the advantages of SSUKF and EKF, improves the computational efficiency, insures the estimation precision and robustness, therefore it is more suitable for the spacecraft autonomous navigation system.