Abstract
Electronic support measure (ESM) can detect the bearings and Doppler frequencies simultaneously. A target tracking algorithm is proposed which uses ESM’s Doppler frequency and bearing measurements using extended Kalman filter (EKF). Compared with traditional bearings-only target tracking methods, our algorithm increases the Doppler frequency measurements and introduces the second-order EKF which can preferably handle the nonlinear tracking problem. Finally the simulation results show that the method improves the accuracy of target state estimation as well as the filtering stability. The maneuvers of sensor platform also can be avoided. Monte-Carlo runs with result analysis further illustrate the effectiveness of the algorithm.
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