Trajectory Tracking Based On Iterated Unscented Kalman Filter Of Boost Phase

The trajectory tracking using the satellite LOS measurement faces the problem of weak observability and large initial error. It´s important to induct a robust and fast convergence tracking algorithm. This paper propose a new algorithm IUKF, which improves the estimation of the trajectory state and covariance. It is a nonlinear filter based on the standard kalman filter. Compared with the other methods using the Monte-Carlo simulation, the result shows that the new algorithm has faster convergence speed and higher tracking precision.