Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling

Based on weighted block sparse recovery, a high resolution direction-of-arrival (DOA) estimation algorithm is proposed for data with unknown mutual coupling. In our proposed method, a new block representation model based on the array covariance vectors is firstly formulated to avoid the influence of...

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Main Authors: Meng, Dandan, Wang, Xianpeng, Huang, Mengxing, Shen, Chong, Bi, Guoan
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2019
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Online Access:https://hdl.handle.net/10356/103497
http://hdl.handle.net/10220/47359
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1034972020-03-07T14:00:36Z Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling Meng, Dandan Wang, Xianpeng Huang, Mengxing Shen, Chong Bi, Guoan School of Electrical and Electronic Engineering Unknown Mutual Coupling DRNTU::Engineering::Electrical and electronic engineering DOA Estimation Based on weighted block sparse recovery, a high resolution direction-of-arrival (DOA) estimation algorithm is proposed for data with unknown mutual coupling. In our proposed method, a new block representation model based on the array covariance vectors is firstly formulated to avoid the influence of unknown mutual coupling by utilizing the inherent structure of the steering vector. Then a weighted l1 -norm penalty algorithm is proposed to recover the block sparse matrix, in which the weighted matrix is constructed based on the principle of a novel Capon space spectrum function for increasing the sparsity of solution. Finally, the DOAs can be obtained from the position of the non-zero blocks of the recovered sparse matrix. Due to the use of the whole received data of array and the enhanced sparsity of solution, the proposed method effectively avoids the loss of the array aperture to achieve a better estimation performance in the environment of unknown mutual coupling in terms of both spatial resolution and accuracy. Simulation experiments show the proposed method achieves better performance than other existing algorithms to minimize the effects of unknown mutual coupling. Published version 2019-01-04T02:11:15Z 2019-12-06T21:13:57Z 2019-01-04T02:11:15Z 2019-12-06T21:13:57Z 2018 Journal Article Meng, D., Wang, X., Huang, M., Shen, C., & Bi, G. (2018). Weighted Block Sparse Recovery Algorithm for High Resolution DOA Estimation with Unknown Mutual Coupling. Electronics, 7(10), 217-.doi:10.3390/electronics7100217 https://hdl.handle.net/10356/103497 http://hdl.handle.net/10220/47359 10.3390/electronics7100217 en Electronics © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 13 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Unknown Mutual Coupling
DRNTU::Engineering::Electrical and electronic engineering
DOA Estimation
spellingShingle Unknown Mutual Coupling
DRNTU::Engineering::Electrical and electronic engineering
DOA Estimation
Meng, Dandan
Wang, Xianpeng
Huang, Mengxing
Shen, Chong
Bi, Guoan
Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling
description Based on weighted block sparse recovery, a high resolution direction-of-arrival (DOA) estimation algorithm is proposed for data with unknown mutual coupling. In our proposed method, a new block representation model based on the array covariance vectors is firstly formulated to avoid the influence of unknown mutual coupling by utilizing the inherent structure of the steering vector. Then a weighted l1 -norm penalty algorithm is proposed to recover the block sparse matrix, in which the weighted matrix is constructed based on the principle of a novel Capon space spectrum function for increasing the sparsity of solution. Finally, the DOAs can be obtained from the position of the non-zero blocks of the recovered sparse matrix. Due to the use of the whole received data of array and the enhanced sparsity of solution, the proposed method effectively avoids the loss of the array aperture to achieve a better estimation performance in the environment of unknown mutual coupling in terms of both spatial resolution and accuracy. Simulation experiments show the proposed method achieves better performance than other existing algorithms to minimize the effects of unknown mutual coupling.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Meng, Dandan
Wang, Xianpeng
Huang, Mengxing
Shen, Chong
Bi, Guoan
format Article
author Meng, Dandan
Wang, Xianpeng
Huang, Mengxing
Shen, Chong
Bi, Guoan
author_sort Meng, Dandan
title Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling
title_short Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling
title_full Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling
title_fullStr Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling
title_full_unstemmed Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling
title_sort weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling
publishDate 2019
url https://hdl.handle.net/10356/103497
http://hdl.handle.net/10220/47359
_version_ 1681040644848484352