Trajectory Tracking Based On Iterated Unscented Kalman Filter Of Boost Phase

Abstract

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.