Electromagnetic Imaging of Closely Spaced Objects Using Matching Pursuit Based Approaches

Rifat Volkan Şenyuva; Özgur Özdemir; Güneş Karabulut Kurt; Emin Anarim

doi:10.1109/LAWP.2015.2498702

Electromagnetic Imaging of Closely Spaced Objects Using Matching Pursuit Based Approaches

Rifat Volkan Şenyuva
, Özgur Özdemir
, Güneş Karabulut Kurt
, Emin Anarim

Department of Electronics and Communication Engineering

Bogazici University
Istanbul Technical University

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

In this letter, sparse signal recovery framework is applied for the reconstruction of two closely placed point-like objects from measured scattered electromagnetic field. Greedy matching pursuit-based algorithms are investigated as the sparsity promoting method. The performances of the matching pursuit algorithms are compared against convex relaxation methods. Orthogonal matching pursuit algorithm implemented with a flexible tree structure is shown to improve the resolution for the inverse scattering problem.

Original language	English
Article number	7327171
Pages (from-to)	1179-1182
Number of pages	4
Journal	IEEE Antennas and Wireless Propagation Letters
Volume	15
DOIs	https://doi.org/10.1109/LAWP.2015.2498702
Publication status	Published - 2016

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Compressive sensing
electromagnetic imaging
inverse problems
matching pursuit algorithms

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10.1109/LAWP.2015.2498702

Cite this

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abstract = "In this letter, sparse signal recovery framework is applied for the reconstruction of two closely placed point-like objects from measured scattered electromagnetic field. Greedy matching pursuit-based algorithms are investigated as the sparsity promoting method. The performances of the matching pursuit algorithms are compared against convex relaxation methods. Orthogonal matching pursuit algorithm implemented with a flexible tree structure is shown to improve the resolution for the inverse scattering problem.",

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doi = "10.1109/LAWP.2015.2498702",

language = "English",

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AU - Özdemir, Özgur

AU - Kurt, Güneş Karabulut

AU - Anarim, Emin

PY - 2016

Y1 - 2016

N2 - In this letter, sparse signal recovery framework is applied for the reconstruction of two closely placed point-like objects from measured scattered electromagnetic field. Greedy matching pursuit-based algorithms are investigated as the sparsity promoting method. The performances of the matching pursuit algorithms are compared against convex relaxation methods. Orthogonal matching pursuit algorithm implemented with a flexible tree structure is shown to improve the resolution for the inverse scattering problem.

AB - In this letter, sparse signal recovery framework is applied for the reconstruction of two closely placed point-like objects from measured scattered electromagnetic field. Greedy matching pursuit-based algorithms are investigated as the sparsity promoting method. The performances of the matching pursuit algorithms are compared against convex relaxation methods. Orthogonal matching pursuit algorithm implemented with a flexible tree structure is shown to improve the resolution for the inverse scattering problem.

KW - Compressive sensing

KW - electromagnetic imaging

KW - inverse problems

KW - matching pursuit algorithms

UR - https://www.scopus.com/pages/publications/84971265205

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M3 - Article

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JF - IEEE Antennas and Wireless Propagation Letters

M1 - 7327171

ER -

Electromagnetic Imaging of Closely Spaced Objects Using Matching Pursuit Based Approaches

Abstract

Bibliographical note

Keywords

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