MIMO-radar Waveform Covariance Matrices for High SINR and Low Side-lobe Levels

Handle URI:
http://hdl.handle.net/10754/263772
Title:
MIMO-radar Waveform Covariance Matrices for High SINR and Low Side-lobe Levels
Authors:
Ahmed, Sajid; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
MIMO-radar has better parametric identifiability but compared to phased-array radar it shows loss in signal-to-noise ratio due to non-coherent processing. To exploit the benefits of both MIMO-radar and phased-array two transmit covariance matrices are found. Both of the covariance matrices yield gain in signal-to-interference-plus-noise ratio (SINR) compared to MIMO-radar and have lower side-lobe levels (SLL)'s compared to phased-array and MIMO-radar. Moreover, in contrast to recently introduced phased-MIMO scheme, where each antenna transmit different power, our proposed schemes allows same power transmission from each antenna. The SLL's of the proposed first covariance matrix are higher than the phased-MIMO scheme while the SLL's of the second proposed covariance matrix are lower than the phased-MIMO scheme. The first covariance matrix is generated using an auto-regressive process, which allow us to change the SINR and side lobe levels by changing the auto-regressive parameter, while to generate the second covariance matrix the values of sine function between 0 and $\pi$ with the step size of $\pi/n_T$ are used to form a positive-semidefinite Toeplitiz matrix, where $n_T$ is the number of transmit antennas. Simulation results validate our analytical results.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Communication Theory Lab
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Signal Processing
Issue Date:
29-Dec-2012
DOI:
10.1109/TSP.2014.2307282
Type:
Article
ISSN:
1053-587X
Appears in Collections:
Articles; Communication Theory Lab; Communication Theory Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAhmed, Sajiden
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2012-12-29T11:27:17Z-
dc.date.available2012-12-29T11:27:17Z-
dc.date.issued2012-12-29en
dc.identifier.issn1053-587Xen
dc.identifier.doi10.1109/TSP.2014.2307282en
dc.identifier.urihttp://hdl.handle.net/10754/263772en
dc.description.abstractMIMO-radar has better parametric identifiability but compared to phased-array radar it shows loss in signal-to-noise ratio due to non-coherent processing. To exploit the benefits of both MIMO-radar and phased-array two transmit covariance matrices are found. Both of the covariance matrices yield gain in signal-to-interference-plus-noise ratio (SINR) compared to MIMO-radar and have lower side-lobe levels (SLL)'s compared to phased-array and MIMO-radar. Moreover, in contrast to recently introduced phased-MIMO scheme, where each antenna transmit different power, our proposed schemes allows same power transmission from each antenna. The SLL's of the proposed first covariance matrix are higher than the phased-MIMO scheme while the SLL's of the second proposed covariance matrix are lower than the phased-MIMO scheme. The first covariance matrix is generated using an auto-regressive process, which allow us to change the SINR and side lobe levels by changing the auto-regressive parameter, while to generate the second covariance matrix the values of sine function between 0 and $\pi$ with the step size of $\pi/n_T$ are used to form a positive-semidefinite Toeplitiz matrix, where $n_T$ is the number of transmit antennas. Simulation results validate our analytical results.en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.rightsRead only.en
dc.titleMIMO-radar Waveform Covariance Matrices for High SINR and Low Side-lobe Levelsen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentCommunication Theory Laben
dc.identifier.journalIEEE Transactions on Signal Processingen
dc.eprint.versionPre-printen
dc.contributor.institutionElectronics and Communication Department, Faculty of Engineering, Cairo University, Cairo, Egypten
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorAhmed, Sajiden
kaust.authorAlouini, Mohamed-Slimen
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