Enhanced covariances matrix sparse representation method for DOA estimation

Wei Cui; Tong Qian; Jing Tian

doi:10.1049/el.2014.4519

Enhanced covariances matrix sparse representation method for DOA estimation

Wei Cui, Tong Qian^*, Jing Tian

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

An enhanced covariances sparse representation method for direction-of-arrival (DOA) estimation is proposed. The method can estimate coherent sources with low computation complexity. The cross-Kronecker product terms of the steering vector are introduced as an extra basis to improve the sparse model. Based on the enhanced model and iteration operation, the proposed method has greater precision in multiple coherent sources situations. Compared with several existing DOA estimation methods, simulation experiments have validated the effectiveness of the proposed method.

Original language	English
Pages (from-to)	1288-1290
Number of pages	3
Journal	Electronics Letters
Volume	51
Issue number	16
DOIs	https://doi.org/10.1049/el.2014.4519
Publication status	Published - 6 Aug 2015

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10.1049/el.2014.4519

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title = "Enhanced covariances matrix sparse representation method for DOA estimation",

abstract = "An enhanced covariances sparse representation method for direction-of-arrival (DOA) estimation is proposed. The method can estimate coherent sources with low computation complexity. The cross-Kronecker product terms of the steering vector are introduced as an extra basis to improve the sparse model. Based on the enhanced model and iteration operation, the proposed method has greater precision in multiple coherent sources situations. Compared with several existing DOA estimation methods, simulation experiments have validated the effectiveness of the proposed method.",

author = "Wei Cui and Tong Qian and Jing Tian",

note = "Publisher Copyright: {\textcopyright} The Institution of Engineering and Technology 2015.",

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AU - Qian, Tong

AU - Tian, Jing

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N2 - An enhanced covariances sparse representation method for direction-of-arrival (DOA) estimation is proposed. The method can estimate coherent sources with low computation complexity. The cross-Kronecker product terms of the steering vector are introduced as an extra basis to improve the sparse model. Based on the enhanced model and iteration operation, the proposed method has greater precision in multiple coherent sources situations. Compared with several existing DOA estimation methods, simulation experiments have validated the effectiveness of the proposed method.

AB - An enhanced covariances sparse representation method for direction-of-arrival (DOA) estimation is proposed. The method can estimate coherent sources with low computation complexity. The cross-Kronecker product terms of the steering vector are introduced as an extra basis to improve the sparse model. Based on the enhanced model and iteration operation, the proposed method has greater precision in multiple coherent sources situations. Compared with several existing DOA estimation methods, simulation experiments have validated the effectiveness of the proposed method.

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JO - Electronics Letters

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Enhanced covariances matrix sparse representation method for DOA estimation

Abstract

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