A Low Complexity Localization Algorithm for Mixed Far-Field and Near-Field Sources

被引：10
|
作者：
Huang, Zhikai [1 ]
Xue, Bing [2 ]
Wang, Wei [2 ]
Dong, Fuwang [2 ]
Wang, Di [2 ]
机构：
[1] 28th Res Inst China Elect Technol Grp Corp, Nanjing 210007, Peoples R China
[2] Harbin Engn Univ, Coll Intelligent Syst Sci & Engn, Harbin 150001, Peoples R China
来源：
IEEE COMMUNICATIONS LETTERS | 2021年 / 25卷 / 12期
关键词：
Discrete Fourier transforms; Matching pursuit algorithms; Location awareness; Multiple signal classification; Data mining; Computational complexity; Apertures; Mixed far-field and near-field sources; discrete Fourier transform; orthogonal matching pursuit; array signal processing; sources localization; PASSIVE LOCALIZATION; CLASSIFICATION;
D O I：
10.1109/LCOMM.2021.3114686
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
In this letter, a low complexity localization algorithm based on Discrete Fourier Transform (DFT) and Orthogonal Matching Pursuit (OMP) is proposed for mixed far-field and near-field sources. The angular parameters of mixed sources can be classified and estimated by performing DFT on the anti-diagonal elements of covariance matrix and the received signal. Moreover, the estimated angular parameters and covariance are used to construct a sparse reconstruction problem related with range parameters, which can be solved by OMP algorithm. Furthermore, an iteration method is also proposed to compensate the bias of DFT. Numerical results demonstrate the superiority of proposed localization algorithm.
引用
收藏
页码：3838 / 3842
页数：5
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