Abstract:

The dynamical models of three phases of the ballistic missile (BM) trajectory are rather complicated and strongly nonlinear, how to consecutively track the whole BM trajectory without any prior information has become an urgent problem. To solve this problem, an asymmetric interacting multiple model (AIMM) filter is proposed, which establishes relevant tracking models based on different phases of the ballistic trajectory. The AIMM state interaction and a probability apdated method based on variations in entropy information interacting multiple model (IMM) are used to estimate the real time state of the BM. The algorithm also uses a discrete method to improve one of the unscented Kalman filters (UKF) nonlinear state estimation. Simulation results show that the proposed algorithm can consecutively track the BM from the boost phase till the reentry phase quite precisely; what is more, this algorithm can largely reduce the tracking error during the phase switching.