Low complexity joint estimation of reflection coefficient, spatial location, and Doppler shift for MIMO-radar by exploiting 2D-FFT

Handle URI:
http://hdl.handle.net/10754/565002
Title:
Low complexity joint estimation of reflection coefficient, spatial location, and Doppler shift for MIMO-radar by exploiting 2D-FFT
Authors:
Jardak, Seifallah; Ahmed, Sajid; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
In multiple-input multiple-output (MIMO) radar, to estimate the reflection coefficient, spatial location, and Doppler shift of a target, maximum-likelihood (ML) estimation yields the best performance. For this problem, the ML estimation requires the joint estimation of spatial location and Doppler shift, which is a two dimensional search problem. Therefore, the computational complexity of ML estimation is prohibitively high. In this work, to estimate the parameters of a target, a reduced complexity optimum performance algorithm is proposed, which allow two dimensional fast Fourier transform to jointly estimate the spatial location and Doppler shift. To asses the performances of the proposed estimators, the Cramér-Rao-lower-bound (CRLB) is derived. Simulation results show that the mean square estimation error of the proposed estimators achieve the CRLB. © 2014 IEEE.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Electrical Engineering Program; Communication Theory Lab
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2014 International Radar Conference
Conference/Event name:
2014 International Radar Conference, Radar 2014
Issue Date:
Oct-2014
DOI:
10.1109/RADAR.2014.7060304
Type:
Conference Paper
ISBN:
9781479941957
Appears in Collections:
Conference Papers; Electrical Engineering Program; Communication Theory Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorJardak, Seifallahen
dc.contributor.authorAhmed, Sajiden
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2015-08-04T07:27:49Zen
dc.date.available2015-08-04T07:27:49Zen
dc.date.issued2014-10en
dc.identifier.isbn9781479941957en
dc.identifier.doi10.1109/RADAR.2014.7060304en
dc.identifier.urihttp://hdl.handle.net/10754/565002en
dc.description.abstractIn multiple-input multiple-output (MIMO) radar, to estimate the reflection coefficient, spatial location, and Doppler shift of a target, maximum-likelihood (ML) estimation yields the best performance. For this problem, the ML estimation requires the joint estimation of spatial location and Doppler shift, which is a two dimensional search problem. Therefore, the computational complexity of ML estimation is prohibitively high. In this work, to estimate the parameters of a target, a reduced complexity optimum performance algorithm is proposed, which allow two dimensional fast Fourier transform to jointly estimate the spatial location and Doppler shift. To asses the performances of the proposed estimators, the Cramér-Rao-lower-bound (CRLB) is derived. Simulation results show that the mean square estimation error of the proposed estimators achieve the CRLB. © 2014 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectCramér-Rao lower bounden
dc.subjectDoppleren
dc.subjectMIMO-radaren
dc.subjectReflection coefficienten
dc.subjectSpatial locationen
dc.titleLow complexity joint estimation of reflection coefficient, spatial location, and Doppler shift for MIMO-radar by exploiting 2D-FFTen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentElectrical Engineering Programen
dc.contributor.departmentCommunication Theory Laben
dc.identifier.journal2014 International Radar Conferenceen
dc.conference.date13 October 2014 through 17 October 2014en
dc.conference.name2014 International Radar Conference, Radar 2014en
kaust.authorJardak, Seifallahen
kaust.authorAhmed, Sajiden
kaust.authorAlouini, Mohamed-Slimen
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