A Sparse Representation Method for Coherent Sources Angle Estimation with Uniform Circular Array. (13th October 2019)

• Record Type: Journal Article
• Authors: Su, Xiaolong; Liu, Zhen; Liu, Tianpeng; Peng, Bo; Chen, Xin; Li, Xiang
• Other Names: Mobashsher Ahmed Toaha Academic Editor.
• Is Part Of: International journal of antennas and propagation. Volume 2019(2019)
• Publication Date: 2019-10-13
• Subjects: Electronic apparatus and appliances -- Periodicals; Antennas (Electronics) -- Periodicals; Radio wave propagation -- Periodicals; Antennes (Électronique); Ondes radioélectriques -- Propagation; Antennas (Electronics); Electronic apparatus and appliances; Radio wave propagation; Electronic journals; Periodicals; 621.382405
• DOI: 10.1155/2019/3849791
• Languages: English
• ISSNs: 1687-5869

Abstract

Abstract : Coherent source localization is a common problem in signal processing. In this paper, a sparse representation method is considered to deal with two-dimensional (2D) direction of arrival (DOA) estimation for coherent sources with a uniform circular array (UCA). Considering that objective function requires sparsity in the spatial dimension but does not require sparsity in time, singular value decomposition (SVD) is employed to reduce computational complexity andℓ 2 norm is utilized to renew objective function. After the new objective function is constructed to evaluate residual and sparsity, a second-order cone (SOC) programming is employed to solve convex optimization problem and obtain 2D spatial spectrum. Simulations show that the proposed method can deal with the case of coherent source localization, which has higher resolution than 2D MUSIC method and does not need to estimate the number of coherent sources in advance.