基于OFDM信号的无网格联合时延多普勒估计:一种多电平汉克尔矩阵方法

Ziyu Zhou, Wei Dai
{"title":"基于OFDM信号的无网格联合时延多普勒估计:一种多电平汉克尔矩阵方法","authors":"Ziyu Zhou, Wei Dai","doi":"10.23919/eusipco55093.2022.9909935","DOIUrl":null,"url":null,"abstract":"This paper investigates the problem of joint es-timation of delay, direction of arrival (DoA), and Doppler when an orthogonal frequency-division multiplexing (OFDM) signal is used for probing. A gridless approach is taken where the above three parameters live on a continuous space rather than a discrete grid. A low-rank multilevel Hankel matrix is used to capture the underlying structure of the back-scattered signals. A convex optimization, termed as Hankel nuclear norm minimization (HNNM), is developed for denoising and parameter estimation, and solved by alternating direction method of multi-pliers (ADMM). Simulations demonstrate that HNNM is robust to noise, and can go beyond the minimum separation bound required by another gridless method atomic norm minimization.","PeriodicalId":231263,"journal":{"name":"2022 30th European Signal Processing Conference (EUSIPCO)","volume":"11 13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gridless Joint Delay-DoA-Doppler Estimation Using OFDM Signals: A Multilevel Hankel Matrix Approach\",\"authors\":\"Ziyu Zhou, Wei Dai\",\"doi\":\"10.23919/eusipco55093.2022.9909935\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the problem of joint es-timation of delay, direction of arrival (DoA), and Doppler when an orthogonal frequency-division multiplexing (OFDM) signal is used for probing. A gridless approach is taken where the above three parameters live on a continuous space rather than a discrete grid. A low-rank multilevel Hankel matrix is used to capture the underlying structure of the back-scattered signals. A convex optimization, termed as Hankel nuclear norm minimization (HNNM), is developed for denoising and parameter estimation, and solved by alternating direction method of multi-pliers (ADMM). Simulations demonstrate that HNNM is robust to noise, and can go beyond the minimum separation bound required by another gridless method atomic norm minimization.\",\"PeriodicalId\":231263,\"journal\":{\"name\":\"2022 30th European Signal Processing Conference (EUSIPCO)\",\"volume\":\"11 13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 30th European Signal Processing Conference (EUSIPCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/eusipco55093.2022.9909935\",\"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 30th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/eusipco55093.2022.9909935","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

研究了正交频分复用(OFDM)信号探测时时延、到达方向和多普勒的联合估计问题。采用无网格方法,上述三个参数驻留在连续空间而不是离散网格上。采用低秩多电平汉克尔矩阵捕获后向散射信号的底层结构。提出了一种用于去噪和参数估计的凸优化方法——汉克尔核范数最小化(HNNM),并采用多钳子交替方向法(ADMM)求解。仿真结果表明,HNNM对噪声具有较强的鲁棒性,并且可以超越原子范数最小化方法所要求的最小分离界限。
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
Gridless Joint Delay-DoA-Doppler Estimation Using OFDM Signals: A Multilevel Hankel Matrix Approach
This paper investigates the problem of joint es-timation of delay, direction of arrival (DoA), and Doppler when an orthogonal frequency-division multiplexing (OFDM) signal is used for probing. A gridless approach is taken where the above three parameters live on a continuous space rather than a discrete grid. A low-rank multilevel Hankel matrix is used to capture the underlying structure of the back-scattered signals. A convex optimization, termed as Hankel nuclear norm minimization (HNNM), is developed for denoising and parameter estimation, and solved by alternating direction method of multi-pliers (ADMM). Simulations demonstrate that HNNM is robust to noise, and can go beyond the minimum separation bound required by another gridless method atomic norm minimization.
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
Assessing Bias in Face Image Quality Assessment Electrically evoked auditory steady state response detection in cochlear implant recipients using a system identification approach Uncovering cortical layers with multi-exponential analysis: a region of interest study Phaseless Passive Synthetic Aperture Imaging with Regularized Wirtinger Flow The faster proximal algorithm, the better unfolded deep learning architecture ? The study case of image denoising
×
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