Low Complexity Moving Target Parameter Estimation For MIMO Radar using 2D-FFT

Handle URI:
http://hdl.handle.net/10754/305796
Title:
Low Complexity Moving Target Parameter Estimation For MIMO Radar using 2D-FFT
Authors:
Jardak, Seifallah; Ahmed, Sajid; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
In multiple-input multiple-output radar, to estimate the target parameters, such as the reflection coefficient, spatial location, and Doppler shift, derived cost functions are usually optimized over a grid of points. The performance of such algorithms is directly affected by the grid resolution. Increasing the grid resolution enhances the resolution of the estimator but also increases its computational complexity exponentially. In this work, to estimate the parameters of a target, two reduced complexity optimum performance adaptive algorithms, which are based on Capon and amplitude and phase estimation, are presented. The proposed algorithm exploits the low order two-dimensional fast Fourier transform to determine the sub- optimal estimates of spatial location and Doppler shift, which are then used as the initial points for the derived steepest descent algorithm. In contrast to the grid search based algorithms, the proposed algorithm can optimally estimate on- and off-the-grid targets in very low computational complexity. Simulation results show that the mean-squared estimation error of the proposed estimators achieve the Craḿer-Rao lower bound.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Communication Theory Lab
Publisher:
IEEE Transaction on Signal Processing
Issue Date:
8-Feb-2015
Type:
Article
Appears in Collections:
Articles; 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.accessioned2013-11-26T13:02:21Z-
dc.date.available2013-11-26T13:02:21Z-
dc.date.issued2015-02-08en
dc.identifier.urihttp://hdl.handle.net/10754/305796en
dc.description.abstractIn multiple-input multiple-output radar, to estimate the target parameters, such as the reflection coefficient, spatial location, and Doppler shift, derived cost functions are usually optimized over a grid of points. The performance of such algorithms is directly affected by the grid resolution. Increasing the grid resolution enhances the resolution of the estimator but also increases its computational complexity exponentially. In this work, to estimate the parameters of a target, two reduced complexity optimum performance adaptive algorithms, which are based on Capon and amplitude and phase estimation, are presented. The proposed algorithm exploits the low order two-dimensional fast Fourier transform to determine the sub- optimal estimates of spatial location and Doppler shift, which are then used as the initial points for the derived steepest descent algorithm. In contrast to the grid search based algorithms, the proposed algorithm can optimally estimate on- and off-the-grid targets in very low computational complexity. Simulation results show that the mean-squared estimation error of the proposed estimators achieve the Craḿer-Rao lower bound.en
dc.language.isoenen
dc.publisherIEEE Transaction on Signal Processingen
dc.subjectMIMO-radaren
dc.subjectReflection coefficienten
dc.subjectDoppleren
dc.subjectSpatial locationen
dc.subjectCramer-Rao lower bounden
dc.titleLow Complexity Moving Target Parameter Estimation For MIMO Radar using 2D-FFTen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentCommunication Theory Laben
dc.eprint.versionPre-printen
dc.contributor.institutionDepartment of Physics, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kongen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
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