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Technology of Information Security
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 2
566-569,579

Low-rank matrix recovery based DOA sparse reconstruction method

Fang Yunfei
Wang Hongyan
Pei Bingnan
College of Information Engineering, Dalian University, Dalian Liaoning 116622, China
DOI: 10.19734/j.issn.1001-3695.2017.08.0886

Abstract

To increase the accuracy and resolution of DOA estimation algorithm in the presence of non-uniform noise, based on the low-rank matrix recovery theory, this paper developed a weighted l1 sparse reconstruction DOA estimation algorithm(LR-WLOSRSS) under the second-order statistical domain. Following the low-rank matrix recovery approach, the algorithm firstly introduced the elastic regularization factor to transform the covariance matrix reconstruction problem of the received signal into a semidefinite programming(SDP) one that could be solved very efficiently to reconstruct the noise-free covariance matrix. After that, the DOA could be complemented in the second-order statistical domain by employing the sparse reconstruction weighted l1 norm. Numerical simulations show that, compared to the traditional MUSIC, l1-SVD(l1-norm-singular value decomposition) and weighted l1 methods, the proposed algorithm can suppress the influence of the non-uniform noise significantly, provide better DOA parameter estimation performance, as well as improve angle estimation accuracy and resolution in the case of the low SNR(signal-noise ratio).

Foundation Support

国家自然科学基金资助项目(61301258,61271379)
国家博士后面上资助项目(2016M590218)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.08.0886
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 2
Section: Technology of Information Security
Pages: 566-569,579
Serial Number: 1001-3695(2019)02-054-0566-04

Publish History

[2019-02-05] Printed Article

Cite This Article

房云飞, 王洪雁, 裴炳南. 基于低秩矩阵恢复的DOA稀疏重构方法 [J]. 计算机应用研究, 2019, 36 (2): 566-569,579. (Fang Yunfei, Wang Hongyan, Pei Bingnan. Low-rank matrix recovery based DOA sparse reconstruction method [J]. Application Research of Computers, 2019, 36 (2): 566-569,579. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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