Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

Abdulla Desmal; Hakan Baʇci

Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

Abdulla Desmal, Hakan Baʇci

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.

Original language	English (US)
Title of host publication	2015 9th European Conference on Antennas and Propagation, EuCAP 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9788890701856
State	Published - Aug 27 2015
Event	9th European Conference on Antennas and Propagation, EuCAP 2015 - Lisbon, Portugal Duration: May 13 2015 → May 17 2015

Publication series

Name	2015 9th European Conference on Antennas and Propagation, EuCAP 2015

Conference

Conference	9th European Conference on Antennas and Propagation, EuCAP 2015
Country/Territory	Portugal
City	Lisbon
Period	05/13/15 → 05/17/15

Bibliographical note

Publisher Copyright:
© 2015 EurAAP.

Keywords

Landweber
inverse scattering
microwave imaging
nonlinear iterative shrinkage
sparse optimization

ASJC Scopus subject areas

Instrumentation
Radiation
Computer Networks and Communications

Cite this

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title = "Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding",

abstract = "A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.",

keywords = "Landweber, inverse scattering, microwave imaging, nonlinear iterative shrinkage, sparse optimization",

author = "Abdulla Desmal and Hakan Baʇci",

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year = "2015",

month = aug,

day = "27",

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Desmal, A & Baʇci, H 2015, Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding. in 2015 9th European Conference on Antennas and Propagation, EuCAP 2015., 7228176, 2015 9th European Conference on Antennas and Propagation, EuCAP 2015, Institute of Electrical and Electronics Engineers Inc., 9th European Conference on Antennas and Propagation, EuCAP 2015, Lisbon, Portugal, 05/13/15.

Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding. / Desmal, Abdulla; Baʇci, Hakan.
2015 9th European Conference on Antennas and Propagation, EuCAP 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7228176 (2015 9th European Conference on Antennas and Propagation, EuCAP 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

AU - Desmal, Abdulla

AU - Baʇci, Hakan

PY - 2015/8/27

Y1 - 2015/8/27

N2 - A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.

AB - A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.

KW - Landweber

KW - inverse scattering

KW - microwave imaging

KW - nonlinear iterative shrinkage

KW - sparse optimization

UR - http://www.scopus.com/inward/record.url?scp=84949670276&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84949670276

T3 - 2015 9th European Conference on Antennas and Propagation, EuCAP 2015

BT - 2015 9th European Conference on Antennas and Propagation, EuCAP 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th European Conference on Antennas and Propagation, EuCAP 2015

Y2 - 13 May 2015 through 17 May 2015

ER -

Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

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