基于雷达辅助知识的微弱目标跟踪算法研究

发布时间：2018-06-09 15:07

本文选题：雷达辅助知识 + 微弱目标　；参考：《电子科技大学》2015年硕士论文

【摘要】：随着雷达探测目标的多样化和监测环境的日益复杂化,现有雷达对低空、隐身目标等微弱目标的跟踪性能不能满足工程应用需求。通过充分挖掘各种目标和环境的先验知识,基于雷达辅助知识的跟踪算法能够获得更多信息来提高目标和杂波的区分度,并采取相应策略来改善复杂环境下微弱目标的跟踪性能。这项技术已是国内外目标跟踪领域的研究热点。针对以上问题,本论文主要研究现有幅度知识辅助跟踪的优化算法、基于雷达极化知识的跟踪算法以及地理信息系统辅助跟踪算法和满足工程应用的雷达杂波库辅助的检测跟踪算法。本文具体内容如下:1.针对现有基于雷达幅度知识的跟踪算法在抑制虚假航迹性能上的不足,研究了基于雷达幅度知识的修正跟踪算法,并分析了其跟踪不同起伏目标和不同杂波背景下的性能。该算法利用幅度知识严格了航迹管理准则,优化了原有算法抑制虚假航迹的性能。2.针对极化雷达系统中极化知识在跟踪领域研究甚少的问题,提出了基于雷达极化知识的跟踪算法,其有效改善微弱目标的跟踪精度;在此基础上,结合第二章的修正跟踪算法思想,提出了修正的极化知识辅助跟踪算法,改善了抑制虚假航迹的性能。3.针对复杂环境下目标跟踪回波中存在大量杂波严重影响跟踪性能的问题,研究了地理信息系统辅助跟踪算法,其能够调用监测环境的杂波分类先验信息,从而调整航迹处理的相关策略,其有效改善了复杂环境下抑制虚假航迹的性能。4.针对复杂环境下目标跟踪抑制虚假航迹性能不能满足工程应用的问题,提出了系统性的实践方案即基于雷达杂波库的检测跟踪算法,其将雷达杂波库、知识辅助检测和知识辅助跟踪有效结合在一起,可大幅减低虚假航迹条数,满足目标跟踪工程应用的要求。上述算法已通过仿真实验或雷达实测数据验证,结果表明所研究算法对于改善复杂环境微弱目标的跟踪性能的有效性。
[Abstract]:With the diversification of radar detection targets and the increasing complexity of monitoring environment, the tracking performance of low altitude, stealth targets and other weak targets can not meet the needs of engineering applications. By fully mining the prior knowledge of various targets and environments, the tracking algorithm based on radar auxiliary knowledge can obtain more information to improve the classification of target and clutter. Corresponding strategies are adopted to improve the tracking performance of weak targets in complex environments. This technology has been the research hotspot in the field of target tracking at home and abroad. In view of the above problems, this paper mainly studies the existing amplitude knowledge aided tracking optimization algorithm. The tracking algorithm based on the knowledge of radar polarization, the auxiliary tracking algorithm of geographic information system and the detection and tracking algorithm of radar clutter library for engineering applications. The content of this paper is as follows: 1. Aiming at the deficiency of the existing tracking algorithms based on radar amplitude knowledge in suppressing false track, the modified tracking algorithm based on radar amplitude knowledge is studied, and the performance of the algorithm in tracking different undulating targets and different clutter background is analyzed. The algorithm uses amplitude knowledge to strictly control track management criteria, and optimizes the performance of the original algorithm to suppress false track. A tracking algorithm based on polarimetric knowledge is proposed to improve the tracking accuracy of weak targets effectively, aiming at the problem that the polarimetric knowledge in polarimetric radar system is seldom studied in the field of tracking. Based on the idea of modified tracking algorithm in Chapter 2, a modified polarization knowledge aided tracking algorithm is proposed, which improves the performance of false track suppression. In order to solve the problem that a large number of clutter seriously affect the tracking performance of target tracking echo in complex environment, a geographic information system (GIS) aided tracking algorithm is studied, which can call the prior information of clutter classification in monitoring environment. Therefore, the related strategies of track processing can be adjusted to improve the performance of false track suppression in complex environments. In view of the problem that the performance of target tracking and suppressing false track in complex environment can not meet the problem of engineering application, a systematic practical scheme, that is, detection and tracking algorithm based on radar clutter library, is proposed. The combination of knowledge aided detection and knowledge aided tracking can greatly reduce the number of false tracks and meet the requirements of target tracking engineering applications. The above algorithms have been verified by simulation experiments or radar measurements. The results show that the proposed algorithm is effective in improving the tracking performance of weak targets in complex environments.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN953

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