Stereo vision based relative state estimation for non-cooperative spacecraft with outliers

Abstract

This paper proposes a theory based on stereovision to estimate the relative position and attitude between non-cooperative spacecrafts. Good performance of the scheme can be presented even with outliers in real time observation. As the information of non-cooperative spacecraft in space is not accessible, a full consideration to the target freely tumbling in space is given. Firstly, relative position and orientation equation is derived from target's dynamics model. The extended Kalman filter (EKF) is designed to estimate the relative position and relative attitude by using the observation data provided by stereovision system. In addition, the full-dimensional state estimator is used to improve the precious of the relative position estimation. Furthermore, M-estimation is applied to improve the robustness and reliability of the previous mentioned algorithms. Simulation results demonstrate the effectiveness and convergence of the proposed algorithm. The filtering algorithms with M-estimation can effectively improve the accuracy of relative navigation for non-cooperative spacecraft when the images data is affected by outliers.