Kalman filter based on intermediate transition state for radar target tracking with nonlinear measurements

Abstract

Aiming at the nonlinear measurements problem of target tracking, a Kalman filter algorithm based on intermediate transition state (ITS-KF) is proposed in this paper. The new intermediate transition states are introduced in two- and three-dimension scenarios, and the derivations of state transition between the state in Cartesian coordinate and intermediate transition state in measurement coordinate are given. Based on the intermediate transition state, a new ITS-KF algorithm is proposed and the filtering process is given. For maneuvering target tracking case, ITS-KF is combined with the improved IMM (IIMM) and the ITS-KF-IIMM is given. The simulation results show that the tracking accuracy and consistency of the proposed algorithm is obviously improved compared with existing algorithms especially in the case of large angle measurement errors both in non-maneuvering and maneuvering case.