A Multi-Frame Joint Tracking and Classification Method for Weak Target in Radar System
Wěi Zhāng, Kai Zeng, Chuan Rui Zhu, Xingyue Long, Wei Yi · 2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS) · 2022
This paper solves the problem of joint tracking and classification of weak targets using multi-frame joint processing technology. Weak targets are easily submerged in background noise, and single-frame threshold detection makes many of their feature information lost, making it challenging to track and classify them effectively. Aiming at solving these problems, a multi-frame joint tracking and classification (MF-JTC) method is proposed. The method achieves the accurate estimation of the motion trajectory and target class by jointly processing the radar measurement data in multi-frames. Finally, the results show that compared with the traditional single-frame joint tracking and classification (SF-JTC) method, the proposed method has better tracking and classification performance for weak targets.