A Multi-Frame Joint Tracking and Classification Method for Weak Target in Radar System

W. Zhang, Kai Zeng, Chuan Zhu, Xingyue Long, Wei Yi
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Abstract

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.
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雷达系统弱目标多帧联合跟踪与分类方法
本文采用多帧联合处理技术解决了弱目标的联合跟踪与分类问题。弱目标容易被淹没在背景噪声中,单帧阈值检测使目标的许多特征信息丢失,给目标的有效跟踪和分类带来了挑战。针对这些问题,提出了一种多帧联合跟踪分类(MF-JTC)方法。该方法通过对多帧雷达测量数据进行联合处理,实现对运动轨迹和目标类别的准确估计。最后,实验结果表明,与传统的单帧联合跟踪与分类(SF-JTC)方法相比,本文方法对弱目标具有更好的跟踪与分类性能。
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