Open AccessReweighted nuclear norm minimisation for DOA estimation with unknown mutual coupling
Author(s) -
Meng Dandan,
Wang Xianpeng,
Huang Mengxing,
Yin Yue,
Shen Chong,
Zhang Kun
Publication year - 2019
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2018.7632
Subject(s) - minimisation (clinical trials) , algorithm , matrix norm , compressed sensing , mathematics , norm (philosophy) , computer science , mathematical optimization , eigenvalues and eigenvectors , statistics , physics , quantum mechanics , political science , law
A reweighted nuclear norm minimisation algorithm by considering the inherent rank sparsity of the submatrix block for direction‐of‐arrival (DOA) estimation with unknown mutual coupling in a uniform linear array (ULA) is proposed. A novel block overcomplete dictionary is first derived by parameterising the steering vector to avoid the unknown mutual coupling effect. Then, in order to take advantage of the inherent rank sparsity of the submatrix block, a reweighted nuclear norm minimisation algorithm is introduced, and the weighted matrix can be designed by the Capon spectrum for enhancing the sparsity of scheme. Finally, the DOA estimates can be obtained by the spatial spectrum of the reconstructed matrix. Simulation results verify that the proposed method has distinct advantages over state‐of‐the‐art methods.