基于MUSIC算法的三维多近场源定位提高最优波束形成器的定位精度

Rony Tota, Md. Selim Hossain
{"title":"基于MUSIC算法的三维多近场源定位提高最优波束形成器的定位精度","authors":"Rony Tota, Md. Selim Hossain","doi":"10.1109/ICEEE54059.2021.9718785","DOIUrl":null,"url":null,"abstract":"In this paper the MUSIC source localization algorithm is applied to the near-field narrowband optimal beamformer to increase its localization accuracy and resolution capability. Optimal beamformer cannot identify closely spaced multiple near-field signals. MUSIC algorithm is an Eigen-decomposition based source localization technique. A three dimensional MUSIC algorithm is used with near-field optimal beamformer to correctly localize the three parameters (range, elevation and azimuthal angle) of multiple sources. The robustness of this proposed beamformer against the white Gaussian noisy environment is also examined. The Root Mean Square Error (RMSE) to localize the multiple near-field targets is also studied. The simulation results show that the MUSIC based optimal beamformer can easily sense the multiple closely spaced sources in the noisy environment with sharper radiation lobe using minimum number of snapshots and sensors.","PeriodicalId":188366,"journal":{"name":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Three Dimentional Multiple Near-field Source Localization Based on MUSIC Algorithm to Increase the Localization Accuracy of Optimal Beamformer\",\"authors\":\"Rony Tota, Md. Selim Hossain\",\"doi\":\"10.1109/ICEEE54059.2021.9718785\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the MUSIC source localization algorithm is applied to the near-field narrowband optimal beamformer to increase its localization accuracy and resolution capability. Optimal beamformer cannot identify closely spaced multiple near-field signals. MUSIC algorithm is an Eigen-decomposition based source localization technique. A three dimensional MUSIC algorithm is used with near-field optimal beamformer to correctly localize the three parameters (range, elevation and azimuthal angle) of multiple sources. The robustness of this proposed beamformer against the white Gaussian noisy environment is also examined. The Root Mean Square Error (RMSE) to localize the multiple near-field targets is also studied. The simulation results show that the MUSIC based optimal beamformer can easily sense the multiple closely spaced sources in the noisy environment with sharper radiation lobe using minimum number of snapshots and sensors.\",\"PeriodicalId\":188366,\"journal\":{\"name\":\"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEEE54059.2021.9718785\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Electrical & Electronic Engineering (ICEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE54059.2021.9718785","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文将MUSIC源定位算法应用于近场窄带最优波束形成器,提高了其定位精度和分辨率。最优波束形成器不能识别密集间隔的多个近场信号。MUSIC算法是一种基于特征分解的源定位技术。采用三维MUSIC算法和近场最优波束形成器对多源的距离、仰角和方位角三个参数进行了正确定位。研究了该波束形成器对高斯白噪声环境的鲁棒性。研究了多目标近场定位的均方根误差(RMSE)方法。仿真结果表明,基于MUSIC的最优波束形成器可以在噪声环境中使用最少的快照个数和传感器个数,较好地检测到辐射瓣较清晰的多个紧密间隔源。
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
Three Dimentional Multiple Near-field Source Localization Based on MUSIC Algorithm to Increase the Localization Accuracy of Optimal Beamformer
In this paper the MUSIC source localization algorithm is applied to the near-field narrowband optimal beamformer to increase its localization accuracy and resolution capability. Optimal beamformer cannot identify closely spaced multiple near-field signals. MUSIC algorithm is an Eigen-decomposition based source localization technique. A three dimensional MUSIC algorithm is used with near-field optimal beamformer to correctly localize the three parameters (range, elevation and azimuthal angle) of multiple sources. The robustness of this proposed beamformer against the white Gaussian noisy environment is also examined. The Root Mean Square Error (RMSE) to localize the multiple near-field targets is also studied. The simulation results show that the MUSIC based optimal beamformer can easily sense the multiple closely spaced sources in the noisy environment with sharper radiation lobe using minimum number of snapshots and sensors.
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
Computer-Aided Polyp Removal Detection in Endoscopic Images FPGA based Histogram Equalization for Image Processing Spreading Loss Model for Channel Characterization of Future 6G Terahertz Communication Networks Impact of Cladding Rectangular Bars on the Antiresonant Hollow Core Fiber Predicting Autism Spectrum Disorder Based On Gender Using Machine Learning Techniques
×
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