Reference : Cramer-Rao Bound on DOA Estimation of Finite Bandwidth Signals Using a Moving Sensor

	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/10993/45438

Title :	Cramer-Rao Bound on DOA Estimation of Finite Bandwidth Signals Using a Moving Sensor
Language :	English
Author, co-author :	Arora, Aakash [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 >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2020
Main document title :	Proc. 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Peer reviewed :	Yes
Event name :	45th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2020, 4-8 May 2020, Barcelona, Spain
Event date :	04-05-2020 to 08-05-2020
Event organizer :	IEEE
Event place (city) :	Barcelona
Event country :	Spain
Abstract :	[en] In this paper, we provide a framework for the direction of arrival (DOA) estimation using a single moving sensor and evaluate performance bounds on estimation. We introduce a signal model which captures spatio-temporal incoherency in the received signal due to sensor motion in space and finite bandwidth of the signal, hitherto not considered. We show that in such a scenario, the source signal covariance matrix becomes a function of the source DOA, which is usually not the case. Due to this unknown dependency, traditional subspace techniques cannot be applied and conditions on source covariance needs to imposed to ensure identifiability. This motivates us to investigate the performance bounds through the Cramer-Rao Lower Bounds (CRLBs) to set benchmark performance for future estimators. This paper exploits the signal model to derive an appropriate CRLB, which is shown to be better than those in relevant literature.
Permalink :	http://hdl.handle.net/10993/45438
FnR project :	FnR ; FNR11607283 > Aakash Arora > > Power efficient sparse signal processing for digital wideband on-board techniques > 01/07/2017 > 30/06/2021 > 2017

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