Trajectory estimation in boost phase of passive detection based on dynamic characteristic template

Abstract

An Unscented Kalman Filter with multi model adaptive estimation algorithm (MMAE-UKF) based on dynamic characteristic template is proposed to solve the problem of trajectory estimation of interceptor in boost phase by using passive detection method for single aircraft. Under the condition of incomplete observation information, by introducing the interceptor dynamic characteristic template, the design parameters of flight program model and launch azimuth angle are expanded to target state components. Based on the flight program model and dynamic characteristic template, a nonlinear MMAE model set is constructed. The flight program model and design parameters of the interceptor are identified using the MMAE-UKF algorithm, and the motion state of the interceptor in boost phase is estimated. The simulation results show that the algorithm can quickly and accurately identify the flight program model and design parameters used in the boost phase of the interceptor. Compared with the traditional expanded state filtering algorithm, the motion state estimation error is significantly reduced, and the filtering stability speed is greatly improved.

Keywords

• boost phase|dynamic characteristic template|flight program model|mmae-ukf algorithm