未知源数共阵的DOA估计方法

Anh-Tuan Nguyen, T. Matsubara, T. Kurokawa
{"title":"未知源数共阵的DOA估计方法","authors":"Anh-Tuan Nguyen, T. Matsubara, T. Kurokawa","doi":"10.1109/ICSIGSYS.2017.7967062","DOIUrl":null,"url":null,"abstract":"In the present paper, we consider a co-array as a coprime array or a nested array. Pal et al. proposed a method to extend a co-array to a larger virtual array, then implemented the spatial smoothing technique to construct the covariance matrix of a virtual uniform linear array (ULA). Thus subspace-based direction of arrival (DOA) estimation algorithms can be used to detect more sources than the number of array elements. However, since the subspace-based DOA estimation methods are applied, the DOA estimation accuracy depends on the performance of source number estimation. By employing a set of Toeplitz matrices, we propose a DOA estimation method for co-array, which does not need to know the number of sources prior to computing the spatial spectrum. Computer simulations are provided to demonstrate effectiveness of the proposed approach.","PeriodicalId":212068,"journal":{"name":"2017 International Conference on Signals and Systems (ICSigSys)","volume":"970 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"DOA estimation method for co-arrays with unknown number of sources\",\"authors\":\"Anh-Tuan Nguyen, T. Matsubara, T. Kurokawa\",\"doi\":\"10.1109/ICSIGSYS.2017.7967062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the present paper, we consider a co-array as a coprime array or a nested array. Pal et al. proposed a method to extend a co-array to a larger virtual array, then implemented the spatial smoothing technique to construct the covariance matrix of a virtual uniform linear array (ULA). Thus subspace-based direction of arrival (DOA) estimation algorithms can be used to detect more sources than the number of array elements. However, since the subspace-based DOA estimation methods are applied, the DOA estimation accuracy depends on the performance of source number estimation. By employing a set of Toeplitz matrices, we propose a DOA estimation method for co-array, which does not need to know the number of sources prior to computing the spatial spectrum. Computer simulations are provided to demonstrate effectiveness of the proposed approach.\",\"PeriodicalId\":212068,\"journal\":{\"name\":\"2017 International Conference on Signals and Systems (ICSigSys)\",\"volume\":\"970 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Signals and Systems (ICSigSys)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIGSYS.2017.7967062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Signals and Systems (ICSigSys)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIGSYS.2017.7967062","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

在本文中,我们把协数组看作是一个互素数数组或一个嵌套数组。Pal等人提出了一种将协阵扩展到更大的虚拟阵的方法,然后利用空间平滑技术构建虚拟均匀线性阵(ULA)的协方差矩阵。因此,基于子空间的到达方向估计算法可以用于检测比阵列元素数量更多的源。然而,由于采用了基于子空间的DOA估计方法,DOA估计的精度取决于源数估计的性能。利用一组Toeplitz矩阵,提出了一种不需要知道源个数就可以计算空间频谱的共阵DOA估计方法。计算机仿真验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DOA estimation method for co-arrays with unknown number of sources
In the present paper, we consider a co-array as a coprime array or a nested array. Pal et al. proposed a method to extend a co-array to a larger virtual array, then implemented the spatial smoothing technique to construct the covariance matrix of a virtual uniform linear array (ULA). Thus subspace-based direction of arrival (DOA) estimation algorithms can be used to detect more sources than the number of array elements. However, since the subspace-based DOA estimation methods are applied, the DOA estimation accuracy depends on the performance of source number estimation. By employing a set of Toeplitz matrices, we propose a DOA estimation method for co-array, which does not need to know the number of sources prior to computing the spatial spectrum. Computer simulations are provided to demonstrate effectiveness of the proposed approach.
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
×
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