Reference : A Statistically Efficient Estimator for Co-array Based DoA Estimation

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/37660

Title :	A Statistically Efficient Estimator for Co-array Based DoA Estimation
Language :	English
Author, co-author :	Sedighi, Saeid [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Shankar, Bhavani [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	Oct-2018
Main document title :	Asilomar Conference on Signals, Systems, and Computers
Peer reviewed :	Yes
Audience :	International
Event name :	Asilomar Conference on Signals, Systems, and Computers
Event date :	28-10-108 to 31-10-2018
Keywords :	[en] Co-array Based DoA Estimation ; Sparse arrays ; Cramer-Rao Bound (CRB)
Abstract :	[en] Co-array-based Direction of Arrival (DoA) estimation using Sparse linear arrays (SLAs) has recently gained considerable interest in array processing due to the attractive capability of providing enhanced degrees of freedom. Although a variety of estimators have been suggested in the literature for co-array-based DoA estimation, none of them are statistically efficient. This work introduces a novel Weighted Least Squares (WLS) estimator for the co-array-based DoA estimation employing the covariance fitting method. Then, an optimal weighting is given so that the asymptotic performance of the proposed WLS estimator coincides with the Cram\'{e}r-Rao Bound (CRB), thereby ensuring statistical efficiency of resulting WLS estimator. This implies that the proposed WLS estimator has significantly better performance compared to existing methods in the literature. Numerical simulations are provided to corroborate the asymptotic statistical efficiency and the improved performance of the proposed estimator.
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/10993/37660
DOI :	10.1109/ACSSC.2018.8645246
FnR project :	FnR ; FNR11228830 > Saeid Sedighi > > Compressive Sensing for Ranging and Detection in Automotive Applications > 15/02/2017 > 14/02/2021 > 2016

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