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• W1498133965 abstract "The paper deals with sparsely sampled nonstationary signals in a multi-sensor array platform. We examine direction-of-arrival (DOA) estimation using sparsity-based time-frequency signal representation (TFSR). While conventional time-frequency analysis techniques suffer from noise-like artifacts due to missing data samples, high-fidelity time-frequency signatures can be obtained by applying kernelled processing and sparse reconstruction. Since the signals received at different sensors occupy the same time-frequency regions and share a common nonzero support, the recovery of TFSRs can be cast as a group sparse reconstruction problem. The reconstructed auto- and cross-sensor TFSRs enable the formation of the spatial time-frequency distribution (STFD) matrix, which is used, in turn, to propose the sparse time-frequency MUSIC (STF-MUSIC). The proposed STF-MUSIC method achieves effective source discrimination capability, leading to improved DOA estimation performance." @default.
• W1498133965 created "2016-06-24" @default.
• W1498133965 creator A5007661434 @default.
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• W1498133965 date "2015-07-01" @default.
• W1498133965 modified "2023-09-27" @default.
• W1498133965 title "DOA estimation of sparsely sampled nonstationary signals" @default.
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• W1498133965 doi "https://doi.org/10.1109/chinasip.2015.7230412" @default.
• W1498133965 hasPublicationYear "2015" @default.
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