A single maneuvering target tracking algorithm based on STUKF for automotive radar

Kai Jiang; JianJiang Zhou

doi:10.1117/12.2631820

14 April 2022 A single maneuvering target tracking algorithm based on STUKF for automotive radar

Kai Jiang, JianJiang Zhou

Proceedings Volume 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021); 121781Q (2022) https://doi.org/10.1117/12.2631820
Event: International Conference on Signal Processing and Communication Technology (SPCT 2021), 2021, Tianjin, China

Abstract

Aiming at the hidden danger caused by the extensive application of automotive radar, an improved single maneuvering target tracking algorithm of automotive radar is proposed in this paper, and its research and simulation are carried out. In automotive radar applications, the movement of a single model does not accurately describe the motion of target relative to the radar, in order to improve the accuracy of the description of target motion state, this article put forward the Interactive Multiple Model Strong Tracking Unscented Kalman Filter (IMM - STUKF) algorithm, this algorithm not only solves the problem of imprecise description of the actual motion state of the target, it also makes up for the poor robustness of traditional UKF algorithm and ensures the tracking accuracy of single maneuvering target. Experimental simulation results show that the proposed algorithm can reduce tracking error more effectively than the traditional IMM-UKF algorithm.

Citation Download Citation

Kai Jiang and JianJiang Zhou "A single maneuvering target tracking algorithm based on STUKF for automotive radar", Proc. SPIE 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021), 121781Q (14 April 2022); https://doi.org/10.1117/12.2631820

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