Covariance sparsity-aware DOA estimation for nonuniform noise

Authors:
Zhen-Qing He;Zhi-Ping Shi;Lei Huang
Affiliations:
National Key Laboratory of Communications, University of Electronic Science and Technology of China, Chengdu, China;National Key Laboratory of Communications, University of Electronic Science and Technology of China, Chengdu, China;Department of Electronic and Information Engineering, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China
Venue:
Digital Signal Processing
Year:
2014

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Abstract

This paper reformulates the problem of direction-of-arrival (DOA) estimation for unknown nonuniform noise by exploiting a sparse representation of the array covariance vectors. In the proposed covariance sparsity-aware DOA estimator, the unknown noise variances can be eliminated by a linear transformation, and DOA estimation is reduced to a sparse reconstruction problem with nonnegativity constraint. The proposed method not only obtains an extended-aperture array with increased degrees of freedom which enables us to handle more sources than sensors, but also provides superiority in performance and robustness against nonuniform noise. Numerical examples under different conditions demonstrate the effectiveness of the proposed method.