Abstract: Aiming at the turn rate identification of fighter zigzag maneuver in the context of noise at the epoch apart, taking into account the characteristics of the coupling between the target state and turn rate, starting from the joint optimization solution an algorithm for joint estimation and identification with correlated noises at one epoch apart is proposed based on the Expectation Maximization (EM) algorithm. First, the de-correlating framework is utilized to eliminate the correlation between process noise and measurement noise, and thus the problem of turn rate identification with correlated noises at one epoch apart is transformed into the problem of turn rate identification with one-step delayed state. Second, by eliminating the non-linear coupling between the target state and turn rate, joint estimation and identification of both states and turn rate are achieved using the EM algorithm. A closed-loop analytic solution for the turn rate is then achieved:in the E-step, the state of the target and the expectation are achieved accurately by use of the High-degree Cubature Kalman Smoothers (HCKS) with correlated noises at one epoch apart; in the M-step, the analytical identification result of turn rate is obtained by maximizing the expectation. Simulation results show that the algorithm proposed is superior to the traditional augmentation method in terms of state estimation and turn rate identification.

Key words: zigzag maneuver, correlated noises at one epoch apart, de-correlating framework, Expectation Maximization (EM), joint estimation and identification