2020 IEEE 8th International Conference on Information, Communication and Networks (ICICN) 2020
DOI: 10.1109/icicn51133.2020.9205070
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DOA Estimation for Nested Array from Reusing Redundant Virtual Array Elements Viewpoint

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(2 citation statements)
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“…The best-known and fundamental sparse geometry is the nested array (NA) [10], which acquires hole-free lags in the yielding difference co-array, thereby promoting the application and development of the subspace-based techniques [10,[15][16][17]. Afterwards, extensive efforts have been devoted to enhancing the attainable number of uniform DOFs (uDOFs).…”
Section: Introductionmentioning
confidence: 99%
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“…The best-known and fundamental sparse geometry is the nested array (NA) [10], which acquires hole-free lags in the yielding difference co-array, thereby promoting the application and development of the subspace-based techniques [10,[15][16][17]. Afterwards, extensive efforts have been devoted to enhancing the attainable number of uniform DOFs (uDOFs).…”
Section: Introductionmentioning
confidence: 99%
“…Although various approaches, such as compressed sensing (CS) [31], virtual array interpolation [32,33] and sensor array motions [34,35], have been proposed to solve this problem, CS and virtual array interpolation bear a huge computational burden, and sensor array motions require a quasi-stationarity environment where the source locations are considered invariant over array motion of half wavelength or multiples half wavelength. Therefore, the subspace-based techniques such as [10,[15][16][17] are still the most direct and efficient estimation algorithms.…”
Section: Introductionmentioning
confidence: 99%