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Title: Weighted block sparse recovery algorithm for high resolution doa estimation with unknown mutual coupling
Authors: Meng, Dandan
Wang, Xianpeng
Huang, Mengxing
Shen, Chong
Bi, Guoan
Keywords: Unknown Mutual Coupling
DRNTU::Engineering::Electrical and electronic engineering
DOA Estimation
Issue Date: 2018
Source: 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
Series/Report no.: Electronics
Abstract: 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.
Rights: © 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 (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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