Reference : CONSISTENT LEAST SQUARES ESTIMATOR FOR CO-ARRAY-BASED DOA ESTIMATION
Scientific congresses, symposiums and conference proceedings : Poster
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/37677
CONSISTENT LEAST SQUARES ESTIMATOR FOR CO-ARRAY-BASED DOA ESTIMATION
English
Sedighi, Saeid mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Shankar, Bhavani mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Maleki, Sina []
Ottersten, Björn mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Jul-2018
Yes
International
THE TENTH IEEE SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP
08-07-2018 to 11-07-2018
[en] Sparse linear arrays ; directions of arrival estimation ; least squares estimator
[en] Sparse linear arrays (SLAs), such as nested and co-prime arrays,
have the attractive capability of providing enhanced degrees of freedom
by exploiting the co-array model. Accordingly, co-array-based
Direction of Arrivals (DoAs) estimation has recently gained considerable
interest in array processing. The literature has suggested
applying MUSIC on an augmented sample covariance matrix for
co-array-based DoAs estimation. In this paper, we propose a Least
Squares (LS) estimator for co-array-based DoAs estimation employing
the covariance fitting method as an alternative to MUSIC. We
show that the proposed LS estimator provides consistent estimates
of DoAs of identifiable sources for SLAs. Additionally, an analytical
expression for the large sample performance of the proposed
estimator is derived. Numerical results illustrate the finite sample
behavior in relation to the derived analytical expression. Moreover,
the performance of the proposed LS estimator is compared to the
co-array-based MUSIC.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/37677
10.1109/SAM.2018.8448477
https://ieeexplore.ieee.org/abstract/document/8448477
FnR ; FNR11228830 > Saeid Sedighi > > Compressive Sensing for Ranging and Detection in Automotive Applications > 15/02/2017 > 14/02/2021 > 2016

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