Reference : Multi-Target Localization in Asynchronous MIMO Radars Using Sparse Sensing

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/32298

Title :	Multi-Target Localization in Asynchronous MIMO Radars Using Sparse Sensing
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) > >]
	Maleki, Sina [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 :	2017
Main document title :	IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Peer reviewed :	Yes
Audience :	International
Event name :	IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Event date :	10-12-2017 to 13-12-2017
Event organizer :	IEEE
Event place (city) :	Curaçao, Dutch Antilles
Event country :	Netherland
Keywords :	[en] localization ; stepped frequency modulation ; joint range-DoA estimation ; sparse sensing
Abstract :	[en] Multi-target localization, warranted in emerging applications like autonomous driving, requires targets to be perfectly detected in the distributed nodes with accurate range measurements. This implies that high range resolution is crucial in distributed localization in the considered scenario. This work proposes a new framework for multi-target localization, addressing the demand for the high range resolution in automotive applications without increasing the required bandwidth. In particular, it employs sparse stepped frequency waveform and infers the target ranges by exploiting sparsity in target scene. The range measurements are then sent to a fusion center where direction of arrival estimation is undertaken. Numerical results illustrate the impact of range resolution on multi-target localization and the performance improvement arising from the proposed algorithm in such scenarios.
Research centres :	Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/10993/32298
DOI :	10.1109/CAMSAP.2017.8313198

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