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Target parameter estimation for spatial and temporal formulations in MIMO radars using compressive sensing

Hussain Ali, Sajid Ahmed, Tareq Y. Al-Naffouri, Mohammad S. Sharawi and Mohamed-S. Alouini

Article (2017)

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Cite this document: Ali, H., Ahmed, S., Al-Naffouri, T. Y., Sharawi, M. S. & Alouini, M.-S. (2017). Target parameter estimation for spatial and temporal formulations in MIMO radars using compressive sensing. EURASIP Journal on Advances in Signal Processing, 2017. doi:10.1186/s13634-016-0436-x
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Abstract

Conventional algorithms used for parameter estimation in colocated multiple-input-multiple-output (MIMO) radars require the inversion of the covariance matrix of the received spatial samples. In these algorithms, the number of received snapshots should be at least equal to the size of the covariance matrix. For large size MIMO antenna arrays, the inversion of the covariance matrix becomes computationally very expensive. Compressive sensing (CS) algorithms which do not require the inversion of the complete covariance matrix can be used for parameter estimation with fewer number of received snapshots. In this work, it is shown that the spatial formulation is best suitable for large MIMO arrays when CS algorithms are used. A temporal formulation is proposed which fits the CS algorithms framework, especially for small size MIMO arrays. A recently proposed low-complexity CS algorithm named support agnostic Bayesian matching pursuit (SABMP) is used to estimate target parameters for both spatial and temporal formulations for the unknown number of targets. The simulation results show the advantage of SABMP algorithm utilizing low number of snapshots and better parameter estimation for both small and large number of antenna elements. Moreover, it is shown by simulations that SABMP is more effective than other existing algorithms at high signal-to-noise ratio.

Uncontrolled Keywords

compressive sensing; mimo radar; colocated

Open Access document in PolyPublie
Subjects: 2500 Génie électrique et électronique > 2502 Électromagnétique, compatibilité et interférence
2500 Génie électrique et électronique > 2511 Antennes et propagation
2500 Génie électrique et électronique > 2522 Radars et navigation
Department: Département de génie électrique
Research Center: Non applicable
Funders: King Abdullah University of Science and Technology (KAUST) - Office of competitive research funding (OCRF), King Fahd University of Petroleum and Minerals (KFUPM) - e Deanship of Scientific Research (DSR)
Grant number: KAUST-002
Date Deposited: 14 Dec 2020 09:44
Last Modified: 08 Apr 2021 10:43
PolyPublie URL: https://publications.polymtl.ca/4744/
Document issued by the official publisher
Journal Title: EURASIP Journal on Advances in Signal Processing (vol. 2017)
Publisher: BioMed Central Ltd
Official URL: https://doi.org/10.1186/s13634-016-0436-x

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