Improved MUSIC Algorithm for Multiple Noncoherent Subarrays

descriptionPublicationkeyboard_double_arrow_right Article 01 May 2014Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Signal Processing Letters, volume 21, pages 527-530 (issn: 1070-9908, eissn: 1558-2361,

Authors: He-Wen Wei; Fei Wen; Rong Fan; Qun Wan;

doi: 10.1109/lsp.2014.2308271

Improved MUSIC Algorithm for Multiple Noncoherent Subarrays

- Summary
- Metrics

Abstract

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.

Related Organizations

University of Electronic Science and Technology of China
China (People's Republic of)
Southwest Research Institute
United States

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	67
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%