基于Hankel矩阵核范数最小化张量补全的MIMO雷达成像方法

Pengcheng Wan, W. Feng, Yanzhong Hao, Hailong Wang
{"title":"基于Hankel矩阵核范数最小化张量补全的MIMO雷达成像方法","authors":"Pengcheng Wan, W. Feng, Yanzhong Hao, Hailong Wang","doi":"10.1109/ICSPCC55723.2022.9984323","DOIUrl":null,"url":null,"abstract":"Multiple input multiple output (MIMO) radar has the ability of multidimensional information sensing. In this paper, a MIMO imaging method under sparse sampling conditions is investigated by constructing a tensor completion algorithm with minimization of the Hankel matrix kernel regularization function. The experiment results show that the MIMO radar system constructed by using the software radio device and the proposed method can effectively image the targets in the scene in three dimensions and reduce the imaging errors under the sparse sampling conditions.","PeriodicalId":346917,"journal":{"name":"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A MIMO Radar Imaging Method Based on Hankel Matrix Nuclear Norm Minimization Tensor Completion\",\"authors\":\"Pengcheng Wan, W. Feng, Yanzhong Hao, Hailong Wang\",\"doi\":\"10.1109/ICSPCC55723.2022.9984323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiple input multiple output (MIMO) radar has the ability of multidimensional information sensing. In this paper, a MIMO imaging method under sparse sampling conditions is investigated by constructing a tensor completion algorithm with minimization of the Hankel matrix kernel regularization function. The experiment results show that the MIMO radar system constructed by using the software radio device and the proposed method can effectively image the targets in the scene in three dimensions and reduce the imaging errors under the sparse sampling conditions.\",\"PeriodicalId\":346917,\"journal\":{\"name\":\"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPCC55723.2022.9984323\",\"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 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCC55723.2022.9984323","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

多输入多输出(MIMO)雷达具有多维信息感知能力。本文通过构造一个最小化汉克尔矩阵核正则化函数的张量补全算法,研究了稀疏采样条件下的MIMO成像方法。实验结果表明,在稀疏采样条件下,利用软件无线电装置和所提方法构建的MIMO雷达系统能够有效地对场景中的目标进行三维成像,减小成像误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A MIMO Radar Imaging Method Based on Hankel Matrix Nuclear Norm Minimization Tensor Completion
Multiple input multiple output (MIMO) radar has the ability of multidimensional information sensing. In this paper, a MIMO imaging method under sparse sampling conditions is investigated by constructing a tensor completion algorithm with minimization of the Hankel matrix kernel regularization function. The experiment results show that the MIMO radar system constructed by using the software radio device and the proposed method can effectively image the targets in the scene in three dimensions and reduce the imaging errors under the sparse sampling conditions.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信