Reference : DoA Estimation Using Low-Resolution Multi-BitSparse Array Measurements

	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/47509

Title :	DoA Estimation Using Low-Resolution Multi-BitSparse Array Measurements
Language :	English
Author, co-author :	Sedighi, Saeid [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Mysore Rama Rao, Bhavani Shankar [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Soltanalian, Mojtaba []
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2021
Journal title :	IEEE Signal Processing Letters
Publisher :	Institute of Electrical and Electronics Engineers
Peer reviewed :	Yes
Audience :	International
ISSN :	1070-9908
Country :	United States
Keywords :	[en] Direction of arrival (DoA) estimation ; low-resolution quantization ; Sparse linear arrays
Abstract :	[en] This letter studies the problem of Direction of Arrival (DoA) estimation from low-resolution few-bit quantized data collected by Sparse Linear Array (SLA). In such cases, contrary to the one-bit quantization case, the well known arcsine law cannot be employed to estimate the covaraince matrix of unquantized array data. Instead, we develop a novel optimization-based framework for retrieving the covaraince matrix of unquantized array data from low-resolution few-bit measurements. The MUSIC algorithm is then applied to an augmented version of the recovered covariance matrix to find the source DoAs. The simulation results show that increasing the sampling resolution to $2$ or $4$ bits per samples could significantly increase the DoA estimation performance compared to the one-bit sampling regime while the power consumption and implementation costs is still much lower in comparison to the high-resolution sampling implementations.
Funders :	Fonds National de la Recherche - FnR
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/10993/47509
DOI :	10.1109/LSP.2021.3090647

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