A nonlinear extended target tracking method based on noncentral inverse Wishart distribution

Abstract

Abstract: To solve the nonlinear extended target tracking problem, a nonlinear extended target tracking method is proposed under the condition of non-central inverse Wishart distribution. First, a non-central inverse Wishart distribution is used to the iterate algorithm under the framework of Bayesian filtering to avoid information loss caused by moment matching or KL divergence minimization. Then, recognizing the limitation of the traditional random matrix (RM) model, which is applicable only under linear observation conditions, the nonlinear measurement information in polar coordinate is linearized by using the de-correlation unbiased transformation algorithm, which ensures the unbiasedness of measurement transformation and avoids the correlation between the transformed measurement covariance estimation and the measurement noise. Furthermore, an effective algorithm for nonlinear extended target tracking based on non-central inverse Wishart distribution is derived. The effectiveness of the proposed method is verified by the tracking simulation of the elliptic extended target.

Key words: extended target tracking, random matrix, non-central inverse Wishart distribution, nonlinear measurement

CLC Number:

TP273

CHEN Hui, WANG Qiu-ju, PENG Tian-shu, ZHAO Yong-hong. A nonlinear extended target tracking method based on noncentral inverse Wishart distribution[J]. Journal of Lanzhou University of Technology, 2025, 51(1): 100-107.

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