宽带 LFM 信号的单源 DOA 估算:时延混合和增强型自混合 MUSIC 方法

IF 1.8 3区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Wentao Zhang, Chen Miao, Mengjie Jiang, Wen Wu
{"title":"宽带 LFM 信号的单源 DOA 估算:时延混合和增强型自混合 MUSIC 方法","authors":"Wentao Zhang, Chen Miao, Mengjie Jiang, Wen Wu","doi":"10.1007/s00034-024-02827-7","DOIUrl":null,"url":null,"abstract":"<p>Accurately estimating the direction of arrival (DOA) of wideband signals with a sensor array is critical in communications, radar, and the Internet of Things. This paper proposes two single-source DOA estimation methods for wideband linear frequency modulation signals: time-delay mixing multiple signal classification (TDM-MUSIC) and enhanced self-mixing MUSIC (ESM-MUSIC). TDM-MUSIC employs time-delay mixing of the received signal to construct an equivalent single-frequency signal model, thereby enhancing estimation accuracy while maintaining reasonable computational efficiency. ESM-MUSIC improves the conventional self-mixing model by adding frequency correction steps, resulting in excellent DOA estimation performance at the expense of computational complexity. Unlike conventional methods that rely on approximate models, our methods establish more accurate equivalent models. A key advantage of our methods is that they allow flexible adjustment of the optimal sensor inter-element spacing in arrays based on the equivalent signal model rather than the actual signal model, simplifying engineering fabrication and reducing mutual coupling between sensors. The paper establishes the Cramér–Rao bounds for both proposed methods and demonstrates their superiority over existing methods through comprehensive numerical simulations. Further, the experiment using a TI-AWR2243 multi-sensor array radar system confirms that our methods are feasible for practical engineering applications.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Single-Source DOA Estimation for Wideband LFM Signal: Time-Delay Mixing and Enhanced Self-Mixing MUSIC Methods\",\"authors\":\"Wentao Zhang, Chen Miao, Mengjie Jiang, Wen Wu\",\"doi\":\"10.1007/s00034-024-02827-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Accurately estimating the direction of arrival (DOA) of wideband signals with a sensor array is critical in communications, radar, and the Internet of Things. This paper proposes two single-source DOA estimation methods for wideband linear frequency modulation signals: time-delay mixing multiple signal classification (TDM-MUSIC) and enhanced self-mixing MUSIC (ESM-MUSIC). TDM-MUSIC employs time-delay mixing of the received signal to construct an equivalent single-frequency signal model, thereby enhancing estimation accuracy while maintaining reasonable computational efficiency. ESM-MUSIC improves the conventional self-mixing model by adding frequency correction steps, resulting in excellent DOA estimation performance at the expense of computational complexity. Unlike conventional methods that rely on approximate models, our methods establish more accurate equivalent models. A key advantage of our methods is that they allow flexible adjustment of the optimal sensor inter-element spacing in arrays based on the equivalent signal model rather than the actual signal model, simplifying engineering fabrication and reducing mutual coupling between sensors. The paper establishes the Cramér–Rao bounds for both proposed methods and demonstrates their superiority over existing methods through comprehensive numerical simulations. Further, the experiment using a TI-AWR2243 multi-sensor array radar system confirms that our methods are feasible for practical engineering applications.</p>\",\"PeriodicalId\":10227,\"journal\":{\"name\":\"Circuits, Systems and Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Circuits, Systems and Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s00034-024-02827-7\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Circuits, Systems and Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s00034-024-02827-7","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

在通信、雷达和物联网领域,利用传感器阵列准确估计宽带信号的到达方向(DOA)至关重要。本文针对宽带线性频率调制信号提出了两种单源 DOA 估算方法:时延混合多信号分类法(TDM-MUSIC)和增强型自混合 MUSIC 法(ESM-MUSIC)。TDM-MUSIC 利用接收信号的时延混合来构建等效的单频信号模型,从而在保持合理计算效率的同时提高估计精度。ESM-MUSIC 通过增加频率校正步骤来改进传统的自混频模型,从而在降低计算复杂度的同时获得出色的 DOA 估计性能。与依赖近似模型的传统方法不同,我们的方法建立了更精确的等效模型。我们的方法的一个主要优势是可以根据等效信号模型而非实际信号模型灵活调整阵列中传感器的最佳元件间距,从而简化工程制造并减少传感器之间的相互耦合。论文通过全面的数值模拟,确定了两种拟议方法的 Cramér-Rao 边界,并证明了它们优于现有方法。此外,使用 TI-AWR2243 多传感器阵列雷达系统进行的实验证实,我们的方法在实际工程应用中是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Single-Source DOA Estimation for Wideband LFM Signal: Time-Delay Mixing and Enhanced Self-Mixing MUSIC Methods

Single-Source DOA Estimation for Wideband LFM Signal: Time-Delay Mixing and Enhanced Self-Mixing MUSIC Methods

Accurately estimating the direction of arrival (DOA) of wideband signals with a sensor array is critical in communications, radar, and the Internet of Things. This paper proposes two single-source DOA estimation methods for wideband linear frequency modulation signals: time-delay mixing multiple signal classification (TDM-MUSIC) and enhanced self-mixing MUSIC (ESM-MUSIC). TDM-MUSIC employs time-delay mixing of the received signal to construct an equivalent single-frequency signal model, thereby enhancing estimation accuracy while maintaining reasonable computational efficiency. ESM-MUSIC improves the conventional self-mixing model by adding frequency correction steps, resulting in excellent DOA estimation performance at the expense of computational complexity. Unlike conventional methods that rely on approximate models, our methods establish more accurate equivalent models. A key advantage of our methods is that they allow flexible adjustment of the optimal sensor inter-element spacing in arrays based on the equivalent signal model rather than the actual signal model, simplifying engineering fabrication and reducing mutual coupling between sensors. The paper establishes the Cramér–Rao bounds for both proposed methods and demonstrates their superiority over existing methods through comprehensive numerical simulations. Further, the experiment using a TI-AWR2243 multi-sensor array radar system confirms that our methods are feasible for practical engineering applications.

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
Circuits, Systems and Signal Processing
Circuits, Systems and Signal Processing 工程技术-工程:电子与电气
CiteScore
4.80
自引率
13.00%
发文量
321
审稿时长
4.6 months
期刊介绍: Rapid developments in the analog and digital processing of signals for communication, control, and computer systems have made the theory of electrical circuits and signal processing a burgeoning area of research and design. The aim of Circuits, Systems, and Signal Processing (CSSP) is to help meet the needs of outlets for significant research papers and state-of-the-art review articles in the area. The scope of the journal is broad, ranging from mathematical foundations to practical engineering design. It encompasses, but is not limited to, such topics as linear and nonlinear networks, distributed circuits and systems, multi-dimensional signals and systems, analog filters and signal processing, digital filters and signal processing, statistical signal processing, multimedia, computer aided design, graph theory, neural systems, communication circuits and systems, and VLSI signal processing. The Editorial Board is international, and papers are welcome from throughout the world. The journal is devoted primarily to research papers, but survey, expository, and tutorial papers are also published. Circuits, Systems, and Signal Processing (CSSP) is published twelve times annually.
×
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