Improved MUSIC Algorithm for Multiple Noncoherent Subarrays

This work addresses the direction-of-arrival (DOA) estimation issue with multiple noncoherent subarrays. We use a maximum likelihood approach to derive a weighted MUSIC (w-MUSIC) algorithm for such arrays, which obtains the overall spatial spectrum via combining the weighted MUSIC spectrum of the su...

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Veröffentlicht in:	IEEE signal processing letters 2014-05, Vol.21 (5), p.527-530
Hauptverfasser:	Wen, Fei, Wan, Qun, Fan, Rong, Wei, Hewen
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Algorithms Arrays Direction Of Arrival (DOA) estimation Direction-of-arrival estimation Maximum likelihood estimation Multiple signal classification MUSIC algorithm noncoherent arrays Sensor arrays Signal processing Signal processing algorithms time varying arrays
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Beschreibung
Zusammenfassung:	This work addresses the direction-of-arrival (DOA) estimation issue with multiple noncoherent subarrays. We use a maximum likelihood approach to derive a weighted MUSIC (w-MUSIC) algorithm for such arrays, which obtains the overall spatial spectrum via combining the weighted MUSIC spectrum of the subarrays. Theoretical analysis and numerical examples demonstrate that the w-MUSIC algorithm has a better performance compared to a previously introduced MUSIC algorithm for noncoherent subarrays.
ISSN:	1070-9908 1558-2361
DOI:	10.1109/LSP.2014.2308271