A Novel Microwave Imaging Approach Based on Regularization in L^ Banach Spaces

Inverse problems arising in microwave imaging suffer from high ill-posedness. As it is well known, it is necessary to employ regularized inversion methods, in order to mitigate such behavior. Usually, such approaches are formulated in standard Hilbert spaces. Recently, a more generic regularization...

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Bibliographic Details
Published inIEEE transactions on antennas and propagation Vol. 60; no. 7; pp. 3373 - 3381
Main Authors Estatico, C., Pastorino, M., Randazzo, A.
Format Journal Article
LanguageEnglish
Published IEEE 01.07.2012
Subjects
Electromagnetics
Equations
Hilbert space
Imaging
Inverse problems
iterative algorithms
Iterative methods
microwave imaging
Minimization
Newton method
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Summary:Inverse problems arising in microwave imaging suffer from high ill-posedness. As it is well known, it is necessary to employ regularized inversion methods, in order to mitigate such behavior. Usually, such approaches are formulated in standard Hilbert spaces. Recently, a more generic regularization theory, working in Banach spaces, has been investigated, in order to overcome some limitations of the Hilbert-space regularization. In this paper, a novel imaging algorithm, performing a L p Banach-space regularization, is proposed for 2-D electromagnetic inverse scattering problems. The reconstruction capabilities of the methods are evaluated by using numerical and experimental data.
ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2012.2196925