Passive localization of mixed sources jointly using MUSIC and sparse signal reconstruction

被引：19

作者：

Tian, Ye ^{[1
]}

Sun, Xiaoying ^{[1
]}

机构：

[1] Jilin Univ, Coll Commun Engn, Changchun 130022, Jilin, Peoples R China

来源：

AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS | 2014年 / 68卷 / 06期

关键词：

Source localization; Sparse representation; MUSIC; Far-field; Near-field; NEAR-FIELD; ESPRIT;

D O I：

10.1016/j.aeue.2013.12.011

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Source localization for mixed far-field and near-field sources is considered. By constructing the second-order statistics domain data of array which is only related to DOA parameters of mixed sources, we obtain the DOA estimation of all sources using the weighted l(1)-norm minimization. And then, we use MUSIC spectral function to distinguish the mixed sources as well as to provide a more accurate DOA estimation of far-field sources. Finally, a mixed overcomplete matrix on the basis of DOA estimation is introduced in the sparse signal representation framework to estimate range parameters. The performance of the proposed method is verified by numerical simulations and is also compared with two existing methods. (C) 2014 Elsevier GmbH. All rights reserved.

引用

页码：534 / 539

页数：6

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