低信噪比下使用阵列反馈波束形成的鲁棒到达方向估计

IF 3.4 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Access Pub Date : 2023-08-01 DOI:10.1109/ACCESS.2023.3300709
Parth Mehta;Kumar Appaiah;Rajbabu Velmurugan
{"title":"低信噪比下使用阵列反馈波束形成的鲁棒到达方向估计","authors":"Parth Mehta;Kumar Appaiah;Rajbabu Velmurugan","doi":"10.1109/ACCESS.2023.3300709","DOIUrl":null,"url":null,"abstract":"A new spatial IIR beamformer based direction-of-arrival (DoA) estimation method is proposed in this paper. We propose a retransmission based spatial feedback method for an array of transmit and receive antennas that improves the performance parameters of a beamformer viz. half-power beamwidth (HPBW), side-lobe suppression, and directivity. Through quantitative comparison we show that our approach outperforms the previous feedback beamforming approach with a single transmit antenna, and the conventional beamformer. We then incorporate a retransmission based minimum variance distortionless response (MVDR) beamformer with the feedback beamforming setup. We propose two approaches, show that one approach is superior in terms of lower estimation error, and use that as the DoA estimation method. We then compare this approach with Multiple Signal Classification (MUSIC), Estimation of Parameters using Rotation Invariant Technique (ESPRIT), robust MVDR, nested-array MVDR, and reduced-dimension MVDR methods. The results show that at SNR levels of \n<inline-formula> <tex-math>$-60\\,\\,\\mathrm { \\text {d} \\text {B} }$ </tex-math></inline-formula>\n to \n<inline-formula> <tex-math>$-10\\,\\,\\mathrm { \\text {d} \\text {B} }$ </tex-math></inline-formula>\n, the angle estiation error of the proposed method is 20° less compared to that of prior methods.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"80647-80655"},"PeriodicalIF":3.4000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10198436.pdf","citationCount":"1","resultStr":"{\"title\":\"Robust Direction-of-Arrival Estimation Using Array Feedback Beamforming in Low SNR Scenarios\",\"authors\":\"Parth Mehta;Kumar Appaiah;Rajbabu Velmurugan\",\"doi\":\"10.1109/ACCESS.2023.3300709\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new spatial IIR beamformer based direction-of-arrival (DoA) estimation method is proposed in this paper. We propose a retransmission based spatial feedback method for an array of transmit and receive antennas that improves the performance parameters of a beamformer viz. half-power beamwidth (HPBW), side-lobe suppression, and directivity. Through quantitative comparison we show that our approach outperforms the previous feedback beamforming approach with a single transmit antenna, and the conventional beamformer. We then incorporate a retransmission based minimum variance distortionless response (MVDR) beamformer with the feedback beamforming setup. We propose two approaches, show that one approach is superior in terms of lower estimation error, and use that as the DoA estimation method. We then compare this approach with Multiple Signal Classification (MUSIC), Estimation of Parameters using Rotation Invariant Technique (ESPRIT), robust MVDR, nested-array MVDR, and reduced-dimension MVDR methods. The results show that at SNR levels of \\n<inline-formula> <tex-math>$-60\\\\,\\\\,\\\\mathrm { \\\\text {d} \\\\text {B} }$ </tex-math></inline-formula>\\n to \\n<inline-formula> <tex-math>$-10\\\\,\\\\,\\\\mathrm { \\\\text {d} \\\\text {B} }$ </tex-math></inline-formula>\\n, the angle estiation error of the proposed method is 20° less compared to that of prior methods.\",\"PeriodicalId\":13079,\"journal\":{\"name\":\"IEEE Access\",\"volume\":\"11 \",\"pages\":\"80647-80655\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/iel7/6287639/10005208/10198436.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Access\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10198436/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10198436/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 1

摘要

提出了一种基于空间IIR波束形成器的DoA估计方法。我们提出了一种基于重传的空间反馈方法,用于发射和接收天线阵列,提高了波束形成器的性能参数,即半功率波束宽度(HPBW),旁瓣抑制和指向性。通过定量比较,我们的方法优于以往的单发射天线反馈波束形成方法和传统波束形成器。然后,我们将基于重传的最小方差无失真响应(MVDR)波束形成器与反馈波束形成装置相结合。我们提出了两种方法,其中一种方法具有较低的估计误差,并将其作为DoA估计方法。然后,我们将该方法与多信号分类(MUSIC)、使用旋转不变量技术(ESPRIT)的参数估计、鲁棒MVDR、嵌套阵列MVDR和降维MVDR方法进行比较。结果表明,在信噪比为$-60\,\,\mathrm {\text {d} \text {B}}$到$-10\,\,\mathrm {\text {d} \text {B}}$的范围内,该方法的角度估计误差比已有方法小20°。
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
Robust Direction-of-Arrival Estimation Using Array Feedback Beamforming in Low SNR Scenarios
A new spatial IIR beamformer based direction-of-arrival (DoA) estimation method is proposed in this paper. We propose a retransmission based spatial feedback method for an array of transmit and receive antennas that improves the performance parameters of a beamformer viz. half-power beamwidth (HPBW), side-lobe suppression, and directivity. Through quantitative comparison we show that our approach outperforms the previous feedback beamforming approach with a single transmit antenna, and the conventional beamformer. We then incorporate a retransmission based minimum variance distortionless response (MVDR) beamformer with the feedback beamforming setup. We propose two approaches, show that one approach is superior in terms of lower estimation error, and use that as the DoA estimation method. We then compare this approach with Multiple Signal Classification (MUSIC), Estimation of Parameters using Rotation Invariant Technique (ESPRIT), robust MVDR, nested-array MVDR, and reduced-dimension MVDR methods. The results show that at SNR levels of $-60\,\,\mathrm { \text {d} \text {B} }$ to $-10\,\,\mathrm { \text {d} \text {B} }$ , the angle estiation error of the proposed method is 20° less compared to that of prior methods.
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
IEEE Access
IEEE Access COMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍: IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest. IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on: Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals. Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering. Development of new or improved fabrication or manufacturing techniques. Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.
期刊最新文献
Corrections to “A Systematic Literature Review of the IoT in Agriculture–Global Adoption, Innovations, Security Privacy Challenges” A Progressive-Assisted Object Detection Method Based on Instance Attention Ensemble Balanced Nested Dichotomy Fuzzy Models for Software Requirement Risk Prediction Enhancing Burn Severity Assessment With Deep Learning: A Comparative Analysis and Computational Efficiency Evaluation Inductor-Less Low-Power Low-Voltage Cross-Coupled Regulated-Cascode Transimpedance Amplifier Circuit in CMOS Technology
×
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