Direction finding for wideband signals using fast coherent signal subspace

M. Frikel, S. Bourennane
{"title":"Direction finding for wideband signals using fast coherent signal subspace","authors":"M. Frikel, S. Bourennane","doi":"10.1109/DSPWS.1996.555529","DOIUrl":null,"url":null,"abstract":"A method to estimate the set of bias vectors spanning the signal subspace without eigendecomposition is described. Each basis vector can be determined by the Lanczos algorithm. The signal subspace estimates at each frequency are transformed by focusing matrices such that the coherent signal subspace will be constructed for all analysis bands. The performance of the proposed method is shown to be almost the same as that of the classical eigendecomposition method.","PeriodicalId":131323,"journal":{"name":"1996 IEEE Digital Signal Processing Workshop Proceedings","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1996 IEEE Digital Signal Processing Workshop Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSPWS.1996.555529","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

A method to estimate the set of bias vectors spanning the signal subspace without eigendecomposition is described. Each basis vector can be determined by the Lanczos algorithm. The signal subspace estimates at each frequency are transformed by focusing matrices such that the coherent signal subspace will be constructed for all analysis bands. The performance of the proposed method is shown to be almost the same as that of the classical eigendecomposition method.
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
基于快速相干信号子空间的宽带信号测向
描述了一种估计跨信号子空间的偏置向量集而不需要特征分解的方法。每个基向量可以通过Lanczos算法确定。通过聚焦矩阵对每个频率的信号子空间估计进行变换,从而为所有分析频带构建相干信号子空间。结果表明,该方法的性能与经典特征分解方法几乎相同。
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
Multirate modeling of human ear frequency resolution for hearing aids An OFDM spread spectrum system using lapped transforms and partial band interference suppression Spectral extrapolation in sub-band coding Memory efficient list based Hough transform for programmable digital signal processors with on-chip caches Towards a system for segmentation under noisy conditions
×
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