Sparse Reconstruction From GPR Data With Applications to Rebar Detection

The problem of detecting and localizing 2-D thin scatterers (i.e., elongated scatterers whose cross sections are small in terms of the probing wavelength) from scattered field measurements is considered. To this end, a linear model that neglects mutual scattering and is based on a distributional rep...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2011-03, Vol.60 (3), p.1070-1079
Main Authors: Soldovieri, F, Solimene, R, Lo Monte, Lorenzo, Bavusi, M, Loperte, A
Format: Article
Language:English
Subjects:
Experiments in realistic conditions
Ground penetrating radar
ground-penetrating radar (GPR)
Image reconstruction
intrawall imaging
inverse scattering
Minimization
Optimization
Scattering
Time domain analysis
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Summary:The problem of detecting and localizing 2-D thin scatterers (i.e., elongated scatterers whose cross sections are small in terms of the probing wavelength) from scattered field measurements is considered. To this end, a linear model that neglects mutual scattering and is based on a distributional representation of the unknown is established. An improved imaging technique based on a minimization algorithm, which takes advantage of the inherent sparseness of the considered ground-penetrating radar scenario, is presented and compared to a classical migration algorithm. The comparison is achieved for both synthetically generated and experimental data collected in realistic conditions under a multimonostatic/multifrequency configuration.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2010.2078310