Autonomous navigation for Mars final approach using X-ray pulsars and Mars network based on RKF

Final approach phase is one of the key phases in Mars landing progress. The performance of the navigation system in this phase influences the actualization of Mars high-precision pinpoint landing. Conventional navigation strategies in this phase mainly rely on the Earth-based measurement, whose time delay is serious because of the long distance between the spacecraft and the ground telemetering station. Therefore, in order to ensure the acquisition of real-time measurement information and enhance the reliability of the navigation system, an autonomous navigation algorithm adopting X-ray pulsars and Mars network is proposed in the current study. This study also considers the atomic clock bias error in the measurement model to further improve the navigation accuracy. Moreover, the rank Kalman filter (RKF) is introduced in the algorithm. Compared with the unscented Kalman filter (UKF), RKF improves the sampling method to obtain optimal state estimations in the filtering process. Numerical simulation results show that the proposed navigation algorithm can make full use of the navigation information provided by X-ray pulsars and Mars network, and can effectively reduce the influence of clock bias errors and guarantee a better performance than conventional methods.