基于四阶统计量稀疏表示的到达方向估计

Shuang Li, Xiaoxiao Jiang, Wei He, Yingguan Wang
{"title":"基于四阶统计量稀疏表示的到达方向估计","authors":"Shuang Li, Xiaoxiao Jiang, Wei He, Yingguan Wang","doi":"10.1109/ICSPCC.2013.6663951","DOIUrl":null,"url":null,"abstract":"In this paper, a new direction of arrival (DOA) estimation method is proposed based on the sparse presentation of array covariance matrix of a difference co-array, which is obtained by exploiting fourth order cumulants. The DOAs are estimated by finding the sparsest solution in a redundant basis. We also give a theoretical guidance to select the regularization parameter. Since fourth order cumulants are used, our method can not only detect more sources than sensors but also can suppress spatially colored noise. Besides, our method achieves higher resolution compared with existing methods. Simulation results are given to demonstrate the effectiveness and excellent performance of the proposed method.","PeriodicalId":124509,"journal":{"name":"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)","volume":"257 11","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Direction of arrival estimation via sparse representation of fourth order statistics\",\"authors\":\"Shuang Li, Xiaoxiao Jiang, Wei He, Yingguan Wang\",\"doi\":\"10.1109/ICSPCC.2013.6663951\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new direction of arrival (DOA) estimation method is proposed based on the sparse presentation of array covariance matrix of a difference co-array, which is obtained by exploiting fourth order cumulants. The DOAs are estimated by finding the sparsest solution in a redundant basis. We also give a theoretical guidance to select the regularization parameter. Since fourth order cumulants are used, our method can not only detect more sources than sensors but also can suppress spatially colored noise. Besides, our method achieves higher resolution compared with existing methods. Simulation results are given to demonstrate the effectiveness and excellent performance of the proposed method.\",\"PeriodicalId\":124509,\"journal\":{\"name\":\"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)\",\"volume\":\"257 11\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPCC.2013.6663951\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCC.2013.6663951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

本文利用四阶累积量得到的差分共阵阵协方差矩阵的稀疏表示,提出了一种新的到达方向估计方法。通过在冗余基础上找到最稀疏的解来估计doa。给出了正则化参数选择的理论指导。由于使用了四阶累积量,该方法不仅可以检测到比传感器更多的源,而且可以抑制空间彩色噪声。此外,与现有方法相比,我们的方法获得了更高的分辨率。仿真结果验证了该方法的有效性和良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Direction of arrival estimation via sparse representation of fourth order statistics
In this paper, a new direction of arrival (DOA) estimation method is proposed based on the sparse presentation of array covariance matrix of a difference co-array, which is obtained by exploiting fourth order cumulants. The DOAs are estimated by finding the sparsest solution in a redundant basis. We also give a theoretical guidance to select the regularization parameter. Since fourth order cumulants are used, our method can not only detect more sources than sensors but also can suppress spatially colored noise. Besides, our method achieves higher resolution compared with existing methods. Simulation results are given to demonstrate the effectiveness and excellent performance of the proposed method.
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