Maneuver sequence planning for autonomous navigation based on multiple asteroid images

During the deep space exploration, position determination is always very important for arriving at the target successfully. But only a little of navigation information can be used by the explorer after it is far away from the Earth. The autonomous navigation using asteroid sequence images provides a new way to solve the position estimation problem for deep space exploration. With more than ten asteroids' optical images, the spacecraft can determine its position autonomously after on-board image processing and computing. This paper focuses on the appropriate navigation asteroid selection and the maneuver sequence planning under the multi-constraints of optical sensors. A new synthesis selection criterion is proposed to evaluate the navigation value considering the influence of visible size, distance, relative velocity, line-of-sight angle and phase angle of asteroids. Based on the optimal performance-cost ratio asteroid set for this navigation, an improved maneuver sequence planning method using generic algorithm is proposed to realize the minimum photo-taking maneuver cost. At last, the simulation results show the advantages of this planning method.