本文对现有的高频地波雷达目标跟踪方法进行了概述，提出了一种地波雷达目标长时连续跟踪的方法，基本思想是：充分挖掘航迹弧段特征，基于特征对船只运动建模，并结合杂波背景进行融合决策。进一步，为了达到长时间连续跟踪的需求，借鉴深度学习的思想，利用新获取的弧段数据对算法估计结果不断递归校正，使得随着获取数据的增加跟踪越准确。该方法适用于杂波环境且在航道附近存在众多干扰船只的情况下对机动目标航迹的实时稳定跟踪，为高频地波雷达在复杂干扰环境下特定目标持续跟踪提供理论基础和方法指导，为充分发挥地波雷达在海上监视监测中的作用提供技术支撑。%In this paper, the typical target tracking methods of high-frequency surface wave radar (HFSWR) are briefly summarized. Subsequently, a method of continuously tracking vessel targets using HFSWR is presented. The basis of this new method is to take full advantage of existing trajectory characteristics, establish a ship motion model based on characteristics and echo data, and make a fusion decision combined with clutter characteristics. Furthermore, in order to satisfy the need of continuous tracking over a long time, the idea of deep learning is ap-plied and the estimation results are recursively corrected with new arc segment data. Therefore, the tracking is more accurate with more obtained data. This method realizes the real-time stable tracking of a maneuvering target trajec-tory in a cluttered environment even in a channel with a lot of ship interference. The method contributes to the theoretical basis and guidance of tracking specific targets with HFSWR continuously and stably and in complex environments with serious clutter/interference. Moreover, the method offers technical support to enable HFSWR play a significant role in maritime surveillance.
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