基于雷达目标极化HRRP特性的舰船目标识别方法

Zhongyuan Lu, Zhongxun Wang, B. Dan
{"title":"基于雷达目标极化HRRP特性的舰船目标识别方法","authors":"Zhongyuan Lu, Zhongxun Wang, B. Dan","doi":"10.1109/PHM-Yantai55411.2022.9941843","DOIUrl":null,"url":null,"abstract":"At present, the progress in broadband and polarimetric measurement technology contributes to a significant advancement of the target identification technology based on HRRP characteristics. This paper focuses on the method used to extract the polarimetric HRRP characteristic of target ships according to the Cloude decomposition theory which is based on the eigenvalue and eigenvector analysis of target coherence matrixes and the Cameron decomposition theory based on the decomposition of Sinclair scattering matrixes. With a clear physical significance, the extracted characteristics can be applied to characterize the target from different angles. By analyzing the divisibility value of them, the characteristics with a high level of divisibility are selected to construct the vectors of the target characteristics. The divisibility and robustness of these characteristics are demonstrated through the simulation of five ship targets, while the effectiveness of the method is verified by the identification results.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ship Target Identification Method based on the Characteristic of Target Polarimetric HRRP of Radars\",\"authors\":\"Zhongyuan Lu, Zhongxun Wang, B. Dan\",\"doi\":\"10.1109/PHM-Yantai55411.2022.9941843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At present, the progress in broadband and polarimetric measurement technology contributes to a significant advancement of the target identification technology based on HRRP characteristics. This paper focuses on the method used to extract the polarimetric HRRP characteristic of target ships according to the Cloude decomposition theory which is based on the eigenvalue and eigenvector analysis of target coherence matrixes and the Cameron decomposition theory based on the decomposition of Sinclair scattering matrixes. With a clear physical significance, the extracted characteristics can be applied to characterize the target from different angles. By analyzing the divisibility value of them, the characteristics with a high level of divisibility are selected to construct the vectors of the target characteristics. The divisibility and robustness of these characteristics are demonstrated through the simulation of five ship targets, while the effectiveness of the method is verified by the identification results.\",\"PeriodicalId\":315994,\"journal\":{\"name\":\"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PHM-Yantai55411.2022.9941843\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHM-Yantai55411.2022.9941843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

目前,宽带和偏振测量技术的进步,使得基于HRRP特性的目标识别技术有了长足的发展。本文重点研究了基于目标相干矩阵特征值和特征向量分析的cloud分解理论和基于Sinclair散射矩阵分解的Cameron分解理论提取目标舰船极化HRRP特征的方法。提取的特征具有明确的物理意义,可用于从不同角度对目标进行表征。通过分析它们的可分性值,选择可分性较高的特征来构建目标特征向量。通过对5个舰船目标的仿真验证了这些特征的可分割性和鲁棒性,并通过识别结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Ship Target Identification Method based on the Characteristic of Target Polarimetric HRRP of Radars
At present, the progress in broadband and polarimetric measurement technology contributes to a significant advancement of the target identification technology based on HRRP characteristics. This paper focuses on the method used to extract the polarimetric HRRP characteristic of target ships according to the Cloude decomposition theory which is based on the eigenvalue and eigenvector analysis of target coherence matrixes and the Cameron decomposition theory based on the decomposition of Sinclair scattering matrixes. With a clear physical significance, the extracted characteristics can be applied to characterize the target from different angles. By analyzing the divisibility value of them, the characteristics with a high level of divisibility are selected to construct the vectors of the target characteristics. The divisibility and robustness of these characteristics are demonstrated through the simulation of five ship targets, while the effectiveness of the method is verified by the identification results.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Abnormal Data Detection Method of Web Database Based on Improved K-Means Algorithm Research on Quantitative Monitoring Method of Milling Tool Wear Condition Based on Multi-Source Data Feature Learning and Extraction Simulation of seasonal variation characteristics of offshore water temperature based on ROMS model Research On Data Mining Of Elderly Inpatients With Chronic Diseases In Panxi Area Badminton Trajectory Accurate Tracking and Positioning Method Based on Machine Vision
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1