Research on Boost-Phase Ballistic Missile Tracking Algorithm Using EM

In this paper, framework of joint optimization algorithm based on EM (Expectation Maximization) is proposed for tracking a boost-phase ballistic target with unknown ballistic parameters. Firstly, the state and unknown parameters are estimated based on smoother in the E step. Then the mean and covariance of initial states, and the noise covariances are calculated in the M step. At last, URTS (Unscented Rauch-Tung-Striebel) based on EM is derived and the analytical forms of unknown statistics parameters are given, which makes the non-convex numerical optimization unnecessary. The result shows that the proposed algorithm is more accurate than iterative UKF (Unscented Kalman Filter) with the same order of magnitude of calculation.