Autonomous Navigation for Deep Spacecraft Based on Celestial Objects

In order to reduce the operation cost of the deep space missions, a new autonomous navigation algorithm based on the observed images information of different celestial objects is proposed. First, it uses the directional data from the moon and the earth sensors to determine the initial orbit information of the explorer by geometrical method. Then combination with the observation from the star tracker, a real-time autonomous navigation for the spacecraft is accomplished via UD factorization Extended Kalman Filter (UD-EKF). Performance and robustness of the algorithm are verified by numerical simulations. The results demonstrate that the algorithm is feasible.