Autonomous relative navigation for noncooperative target using stereo vision measurements

An autonomous relative navigation method based on stereo vision measurements is proposed for noncooperative targets without any prior information. Firstly, a target identification model using only stereo vision measurements is established. Based on the relative position vector computed from the stereo image sequence, the initial state vector of the noncooperative target and navigation filter covariance matrix are initialized by taken spacecraft attitude and camera installation information into account. Then, an extended Kalman filter considering state noise compensation as well as observation variance matrix and state noise matrix adaptive correction is formulated to solve the noncooperative relative navigation problem. Finally, a low Earth orbit, noncooperative target approaching navigation scenario is considered. The simulation results demonstrate the effectiveness of the proposed method for noncooperative autonomous relative navigation.