Open AccessEfficient sparse representation method for wideband DOA estimation using focusing operation
Author(s) -
Zhao Yonghong,
Zhang Linrang,
Gu Yabin,
Guo Yumei,
Zhang Juan
Publication year - 2017
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2017.0061
Subject(s) - wideband , sparse approximation , representation (politics) , computer science , direction of arrival , algorithm , subspace topology , covariance matrix , computational complexity theory , covariance , noise (video) , function (biology) , sparse matrix , mathematics , electronic engineering , engineering , telecommunications , artificial intelligence , statistics , law , political science , politics , physics , quantum mechanics , evolutionary biology , gaussian , antenna (radio) , image (mathematics) , biology
The computational complexity of wideband sparse representation (SR) greatly restricts the application of SR‐based wideband direction‐of‐arrival (DOA) estimation in practical system. Here, an efficient method for wideband direction finding based on SR is proposed. This method combines the focusing operation with weighted subspace fitting (WSF) to not only decrease the computational complexity but also improve the performance of DOA estimation. Exploiting the result of the focusing operation, the covariance matrix at the focusing frequency can be obtained and used as the data for sparse recovery to get wideband DOA estimates. The WSF is employed to reduce the sensitivity to the noise and the regularisation parameter is given by the asymptotic distribution of the WSF cost function. Simulations are provided to show the efficiency and performance of the proposed method.