Abstract
Deep space exploration has significant meaning both in science and economy; however, it is very hard to obtain the relevant information due to its complexity. In this study, the autonomous celestial navigation method is utilised. To achieve high accuracy of the celestial navigation in a deep space environment, the improved filtering algorithm–spherical simplex unscented particle filter (SSUPF) is implemented, which adopts the spherical simplex unscented Kalman filter (SSUKF) algorithm to generate the important sampling density of particle filter (PF). According to simulation results, the authors derive that the SSUPF method can greatly increase the performance of the navigation system compared with unscented Kalman filter (UKF), SSUKF and unscented PF (UPF), and the computational burden of SSUPF is reduced by 24% in comparison with UPF.
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