GRADIENT-BASED SOLUTION OF MAXIMUM LIKELIHOOD ANGLE ESTIMATION FOR VIRTUAL ARRAY MEASUREMENTS

P. Vouras, A. Weiss, Maria Becker, B. Jamroz, J. Quimby, Dylan F. Williams, K. Remley
{"title":"GRADIENT-BASED SOLUTION OF MAXIMUM LIKELIHOOD ANGLE ESTIMATION FOR VIRTUAL ARRAY MEASUREMENTS","authors":"P. Vouras, A. Weiss, Maria Becker, B. Jamroz, J. Quimby, Dylan F. Williams, K. Remley","doi":"10.1109/GlobalSIP.2018.8646422","DOIUrl":null,"url":null,"abstract":"Precise measurement and characterization of millimeter wave channels requires antennas capable of high angular resolution to resolve closely spaced multipath sources. To achieve angular resolution on the order of a few degrees these antennas must be electrically large which is impractical for phased array architectures at millimeter wave frequencies. An alternative approach is to synthesize a virtual aperture in space by using an accurate mechanical positioner to move a receive antenna to points along a sampling grid. An advantage of creating virtual apertures is that the received signal is digitized at every spatial sample position which enables the use of sophisticated angle estimation algorithms such as maximum likelihood (ML) techniques. The main contribution of this paper is a new gradient-based implementation of maximum likelihood angle estimation that was demonstrated on virtual array data collected at 28 GHz using a vector network analyzer (VNA).","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP.2018.8646422","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Precise measurement and characterization of millimeter wave channels requires antennas capable of high angular resolution to resolve closely spaced multipath sources. To achieve angular resolution on the order of a few degrees these antennas must be electrically large which is impractical for phased array architectures at millimeter wave frequencies. An alternative approach is to synthesize a virtual aperture in space by using an accurate mechanical positioner to move a receive antenna to points along a sampling grid. An advantage of creating virtual apertures is that the received signal is digitized at every spatial sample position which enables the use of sophisticated angle estimation algorithms such as maximum likelihood (ML) techniques. The main contribution of this paper is a new gradient-based implementation of maximum likelihood angle estimation that was demonstrated on virtual array data collected at 28 GHz using a vector network analyzer (VNA).
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
基于梯度的虚拟阵列测量最大似然角估计方法
毫米波通道的精确测量和表征需要具有高角分辨率的天线来解析紧密间隔的多径源。为了达到几度的角分辨率,这些天线必须是电大的,这对于毫米波频率的相控阵架构是不切实际的。另一种方法是使用精确的机械定位器将接收天线沿采样网格移动到点上,从而在空间中合成虚拟孔径。创建虚拟孔径的一个优点是,接收到的信号在每个空间样本位置都是数字化的,这使得可以使用复杂的角度估计算法,如最大似然(ML)技术。本文的主要贡献是一种新的基于梯度的最大似然角估计实现,该实现使用矢量网络分析仪(VNA)在28 GHz采集的虚拟阵列数据上进行了演示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION SPATIAL FOURIER TRANSFORM FOR DETECTION AND ANALYSIS OF PERIODIC ASTROPHYSICAL PULSES CNN ARCHITECTURES FOR GRAPH DATA OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS CNN BASED RICIAN K FACTOR ESTIMATION FOR NON-STATIONARY INDUSTRIAL FADING CHANNEL
×
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