A novel central difference Kalman filter with application to spacecraft control

Spacecraft tracking is a very important issue in the domain of spacecraft control. Traditional EKF method can not work well when the system noise is large and initial estimation is less accurate. In order to solve this, a novel central difference Kalman filter based on maximum likehood posterior function is proposed in this paper. The second step of Kalman filter was modified in order to achieve better performance and a typical spacecraft tracking problem is given to show the advances the proposed method.