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• W2036888338 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." @default.
• W2036888338 created "2016-06-24" @default.
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• W2036888338 date "2014-05-01" @default.
• W2036888338 modified "2023-10-16" @default.
• W2036888338 title "Covariance sparsity-aware DOA estimation for nonuniform noise" @default.
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• W2036888338 doi "https://doi.org/10.1016/j.dsp.2014.02.013" @default.
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