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

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

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AU - Anarim, Emin

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KW - Compressive sensing

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KW - inverse problems

KW - matching pursuit algorithms

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Electromagnetic Imaging of Closely Spaced Objects Using Matching Pursuit Based Approaches

Abstract

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Keywords

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