Sparsity-Based Direction Finding of Coherent and Uncorrelated Targets Using Active Nonuniform Arrays
In this letter, direction-of-arrival (DOA) estimation of a mixture of coherent and uncorrelated targets is performed using sparse reconstruction and active nonuniform arrays. The data measurements from multiple transmit and receive elements can be considered as observations from the sum coarray corr...
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Veröffentlicht in: | IEEE signal processing letters 2015-10, Vol.22 (10), p.1628-1632 |
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Sprache: | eng |
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Zusammenfassung: | In this letter, direction-of-arrival (DOA) estimation of a mixture of coherent and uncorrelated targets is performed using sparse reconstruction and active nonuniform arrays. The data measurements from multiple transmit and receive elements can be considered as observations from the sum coarray corresponding to the physical transmit/receive arrays. The vectorized covariance matrix of the sum coarray observations emulates the received data at a virtual array whose elements are given by the difference coarray of the sum coarray (DCSC). Sparse reconstruction is used to fully exploit the significantly enhanced degrees-of-freedom offered by the DCSC for DOA estimation. Simulated data from multiple-input multiple-output minimum redundancy arrays and transmit/receive co-prime arrays are used for performance evaluation of the proposed sparsity-based active sensing approach. |
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ISSN: | 1070-9908 1558-2361 |
DOI: | 10.1109/LSP.2015.2417807 |