Abstract: The rotation parameters of a small body are scientific data, as well as basic data for small body mapping and landing navigation. A small body rotation parameter estimation method is studied based on image feature points tracking and extended Kalman filter in the process of small body exploration approach. The method first establishes a small body's rotation relationship model, which represents the attitude change of the small body in the camera coordinate system; then defines the state equation of the small body's rotation, and pushes to the calculation process of the extended Kalman filter. By tracking the feature points on the observation image sequence, the extended Kalman filter method is used to obtain the estimation of the rotation axis and the rotation angular velocity of the small body. In the experiments, when the distance between the simulated camera and the small body camera is 100km, the initial value of the quaternion between the camera coordinate system and the small body coordinate system, the tracking accuracy of the feature points on the image, and the camera's observation direction are analyzed for the rotation parameters of the small body. The experimental results show that the proposed method can obtain highprecision estimation results.

Key words: small body exploration, rotation parameter estimation, feature tracking, extended Kalman filter