NDLI: Using ℓ1, 2 mixed-norm MUSIC based on compressive sampling for direction of arrival estimation

Content Provider	IEEE Xplore Digital Library
Author	Parian, M.A. Ghofrani, S.
Copyright Year	2015
Description	Author affiliation: Electr. Eng. Dept., Islamic Azad Univ., Tehran, Iran (Parian, M.A.; Ghofrani, S.)
Abstract	High-resolution direction of arrival (DOA) estimation has always been an issue in signal processing field. Most of conventional methods such as Multiple Signal Classification (MUSIC), suffer from lack of resolvability in low signal to noise ratio (SNR) or small number of snapshots whereas computation cost of new methods are considerable. The Compressive MUSIC (CS-MUSIC) algorithm deals with joint sparse problems with employing both array processing and compressive sensing (CS) recovery algorithms to achieve a high-resolution result. In this paper a hybrid method is used for DOA estimation with employing ℓ1, 2 mixed-norm minimization jointly with MUSIC. The performance of the proposed method in terms of resolution and resolvability for both coherent and non-coherent sources is compared with conventional MUSIC and CS-MUSIC. ℓ1,2-MUSIC overcomes the coherency barrier and has high robustness to noise for few numbers of snapshots.
Starting Page	258
Ending Page	263
File Size	1090990
Page Count	6
File Format	PDF
e-ISBN	9781509004812
DOI	10.1109/ISSPIT.2015.7394339
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-07
Publisher Place	United Arab Emirates
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiple signal classification Direction-of-arrival estimation Estimation Signal resolution Arrays Signal to noise ratio Sparse matrices compressive sensing CS-MUSIC ℓ1, 2-MUSIC
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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