Abstract
An algorithm to estimate the tangential and normal accelerations directly using the Doppler radar measurement in an online closed loop form is proposed. Specific works are as follows: first, the tangential acceleration and normal acceleration are taken as the state variables to establish a linear state transition equation; secondly, the decorrelation unbiased conversion measurement Kalman filter (DUCMKF) algorithm is proposed to deal with the strongly nonlinear measurement equation; thirdly, the geometric relationship between the range rate and the velocity direction angle is used to obtain two estimators of the velocity direction angle; finally, the interactive multiple model (IMM) algorithm is used to fuse the estimators of the velocity direction angle and then the adaptive IMM of current statistical model based DUCMKF (AIMM-CS-DUCMKF) is proposed. The simulation experiment results show that the accuracy and stability of DUCMKF are better than the sequential extended Kalman filter algorithm, the sequential unscented Kalman filter algorithm, and converted measurement Kalman filter algorithms; on the other hand they show that the AIMM-CS-DUCMKF can obtain the high accuracy of the tangential and normal accelerations estimation algorithm.
Highlights
In real target motion, the tangential acceleration controls the target velocity size, and the normal acceleration controls the target velocity direction
AIMM-CS-decorrelation unbiased conversion measurement Kalman filter (DUCMKF) proposed is compared with the state of the art interactive multiple model (IMM) algorithm, window-based least squares estimator (WLSE) algorithm, and current statistical model based adaptive EKF (CS-AEKF) algorithm for tracking the maneuvering target and estimating the Maneuvering Accelerations (MAs)
The MAs of the maneuvering target are introduced into the state equation as state variables
Summary
The tangential acceleration controls the target velocity size, and the normal acceleration controls the target velocity direction. The purpose of this paper is to develop a method of directly estimating the MAs of maneuvering target by Doppler radar measurements. This is more practical and meaningful than estimating the ACAs. In the early literature [20], a direct estimation method of the MAs based on the current statistical model is proposed. Combined with the above contents, the adaptive IMM of current statistical model based decorrelation unbiased conversion measurement Kalman filter (AIMM-CS-DUCMKF) algorithm is proposed to estimate the MAs directly in an online closed loop and to improve the tracking performance of the maneuvering target. The results of the discrete state equation are given in Appendix
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