多天线多载波系统的低复杂度 DoA-ToA 信号估计

Chandrashekhar Rai, Debarati Sen
{"title":"多天线多载波系统的低复杂度 DoA-ToA 信号估计","authors":"Chandrashekhar Rai, Debarati Sen","doi":"arxiv-2409.08650","DOIUrl":null,"url":null,"abstract":"Accurate direction of arrival (DoA) and time of arrival (ToA) estimation is\nan stringent requirement for several wireless systems like sonar, radar,\ncommunications, and dual-function radar communication (DFRC). Due to the use of\nhigh carrier frequency and bandwidth, most of these systems are designed with\nmultiple antennae and subcarriers. Although the resolution is high in the large\narray regime, the DoA-ToA estimation accuracy of the practical on-grid\nestimation methods still suffers from estimation inaccuracy due to the spectral\nleakage effect. In this article, we propose DoA-ToA estimation methods for\nmulti-antenna multi-carrier systems with an orthogonal frequency division\nmultiplexing (OFDM) signal. In the first method, we apply discrete Fourier\ntransform (DFT) based coarse signature estimation and propose a low complexity\nmultistage fine-tuning for extreme enhancement in the estimation accuracy. The\nsecond method is based on compressed sensing, where we achieve the\nsuper-resolution by taking a 2D-overcomplete angle-delay dictionary than the\nactual number of antenna and subcarrier basis. Unlike the vectorized 1D-OMP\nmethod, we apply the low complexity 2D-OMP method on the matrix data model that\nmakes the use of CS methods practical in the context of large array regimes.\nThrough numerical simulations, we show that our proposed methods achieve the\nsimilar performance as that of the subspace-based 2D-MUSIC method with a\nsignificant reduction in computational complexity.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Low Complexity DoA-ToA Signature Estimation for Multi-Antenna Multi-Carrier Systems\",\"authors\":\"Chandrashekhar Rai, Debarati Sen\",\"doi\":\"arxiv-2409.08650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Accurate direction of arrival (DoA) and time of arrival (ToA) estimation is\\nan stringent requirement for several wireless systems like sonar, radar,\\ncommunications, and dual-function radar communication (DFRC). Due to the use of\\nhigh carrier frequency and bandwidth, most of these systems are designed with\\nmultiple antennae and subcarriers. Although the resolution is high in the large\\narray regime, the DoA-ToA estimation accuracy of the practical on-grid\\nestimation methods still suffers from estimation inaccuracy due to the spectral\\nleakage effect. In this article, we propose DoA-ToA estimation methods for\\nmulti-antenna multi-carrier systems with an orthogonal frequency division\\nmultiplexing (OFDM) signal. In the first method, we apply discrete Fourier\\ntransform (DFT) based coarse signature estimation and propose a low complexity\\nmultistage fine-tuning for extreme enhancement in the estimation accuracy. The\\nsecond method is based on compressed sensing, where we achieve the\\nsuper-resolution by taking a 2D-overcomplete angle-delay dictionary than the\\nactual number of antenna and subcarrier basis. Unlike the vectorized 1D-OMP\\nmethod, we apply the low complexity 2D-OMP method on the matrix data model that\\nmakes the use of CS methods practical in the context of large array regimes.\\nThrough numerical simulations, we show that our proposed methods achieve the\\nsimilar performance as that of the subspace-based 2D-MUSIC method with a\\nsignificant reduction in computational complexity.\",\"PeriodicalId\":501034,\"journal\":{\"name\":\"arXiv - EE - Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - EE - Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.08650\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08650","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

精确的到达方向(DoA)和到达时间(ToA)估计是声纳、雷达、通信和双功能雷达通信(DFRC)等多种无线系统的严格要求。由于需要使用高载波频率和带宽,这些系统大多采用多天线和子载波设计。虽然大阵列系统的分辨率很高,但由于频谱泄漏效应,实用的网格上估计方法的 DoA-ToA 估计精度仍然存在估计不准的问题。本文提出了具有正交频分复用(OFDM)信号的多天线多载波系统的 DoA-ToA 估计方法。在第一种方法中,我们应用了基于离散傅里叶变换(DFT)的粗特征估计,并提出了一种低复杂度多级微调方法,以极大地提高估计精度。第二种方法基于压缩传感,我们通过获取比实际天线和子载波基数更完整的二维角度-延迟字典来实现超分辨率。与矢量化 1D-OMP 方法不同的是,我们在矩阵数据模型上应用了低复杂度 2D-OMP 方法,这使得 CS 方法在大型阵列环境中的应用变得切实可行。通过数值模拟,我们发现我们提出的方法与基于子空间的 2D-MUSIC 方法性能相似,但计算复杂度显著降低。
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
Low Complexity DoA-ToA Signature Estimation for Multi-Antenna Multi-Carrier Systems
Accurate direction of arrival (DoA) and time of arrival (ToA) estimation is an stringent requirement for several wireless systems like sonar, radar, communications, and dual-function radar communication (DFRC). Due to the use of high carrier frequency and bandwidth, most of these systems are designed with multiple antennae and subcarriers. Although the resolution is high in the large array regime, the DoA-ToA estimation accuracy of the practical on-grid estimation methods still suffers from estimation inaccuracy due to the spectral leakage effect. In this article, we propose DoA-ToA estimation methods for multi-antenna multi-carrier systems with an orthogonal frequency division multiplexing (OFDM) signal. In the first method, we apply discrete Fourier transform (DFT) based coarse signature estimation and propose a low complexity multistage fine-tuning for extreme enhancement in the estimation accuracy. The second method is based on compressed sensing, where we achieve the super-resolution by taking a 2D-overcomplete angle-delay dictionary than the actual number of antenna and subcarrier basis. Unlike the vectorized 1D-OMP method, we apply the low complexity 2D-OMP method on the matrix data model that makes the use of CS methods practical in the context of large array regimes. Through numerical simulations, we show that our proposed methods achieve the similar performance as that of the subspace-based 2D-MUSIC method with a significant reduction in computational complexity.
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
Blind Deconvolution on Graphs: Exact and Stable Recovery End-to-End Learning of Transmitter and Receiver Filters in Bandwidth Limited Fiber Optic Communication Systems Atmospheric Turbulence-Immune Free Space Optical Communication System based on Discrete-Time Analog Transmission User Subgrouping in Scalable Cell-Free Massive MIMO Multicasting Systems Covert Communications Without Pre-Sharing of Side Information and Channel Estimation Over Quasi-Static Fading Channels
×
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