NDLI: Low-complexity direction-of-arrival estimation based on wideband co-prime arrays

Content Provider	ACM Digital Library
Author	Cui, Wei Amin, Moeness G. Wu, Siliang Zhang, Yimin D. Liu, Wei Shen, Qing
Copyright Year	2015
Abstract	A class of low-complexity compressive sensing-based direction-of-arrival (DOA) estimation methods for wideband co-prime arrays is proposed. It is based on a recently proposed narrowband estimation method, where a virtual array model is generated by directly vectorizing the covariance matrix and then using a sparse signal recovery method to obtain the estimation result. As there are a large number of redundant entries in both the auto-correlation and cross-correlation matrices of the two sub-arrays, they can be combined together to form a model with a significantly reduced dimension, thereby leading to a solution with much lower computational complexity without sacrificing performance. A further reduction in complexity is achieved by removing noise power estimation from the formulation. Then, the two proposed low-complexity methods are extended to the wideband realm utilizing a group sparsity based signal reconstruction method. A particular advantage of group sparsity is that it allows a much larger unit inter-element spacing than the standard co-prime array and therefore leads to further improved performance.
Starting Page	1445
Ending Page	1453
Page Count	9
File Format	PDF
ISSN	23299290
e-ISSN	23299304
DOI	10.1109/TASLP.2015.2436214
Volume Number	23
Issue Number	9
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-09-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Co-prime Direction-of-arrival (DOA) estimation Microphone arrays Sparsity Wideband
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

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