DocumentCode
827032
Title
Localizing Thin Metallic Cylinders by a 2.5-D Linear Distributional Approach: Experimental Results
Author
Solimene, Raffaele ; Brancaccio, Adriana ; Romano, Jessica ; Pierri, Rocco
Author_Institution
Dipt. di Ing. dell´´Inf., Seconda Univ. di Napoli, Aversa
Volume
56
Issue
8
fYear
2008
Firstpage
2630
Lastpage
2637
Abstract
The problem of detecting and localizing "thin" metallic scatterers from electromagnetic scattered field measurements is addressed. The scatterers are assumed to be infinitely long and a 2.5-dimensional mathematical model is adopted. According to the distributional approach, the problem is cast as the inversion of a linear integral operator acting on 6-distributions whose supports are representative of the scatterers\´ locations. In this paper we present the experimental validation of such an approach. To this end, we perform the reconstructions by exploiting experimental scattered field data collected in controlled conditions at the electromagnetic diagnostics laboratory of the Second University of Naples. The experiments are conducted in an anechoic chamber where the scatterers are embedded in a homogenous and lossless background medium. The multistatic/single-view/multifrequency and the multistatic/multiview/multifrequency configurations are both considered.
Keywords
anechoic chambers (electromagnetic); electromagnetic wave scattering; integral equations; inverse problems; mathematical operators; 2.5D linear distributional approach; anechoic chamber; electromagnetic scattered field measurement; inversion problem; linear integral operator; mathematical model; multistatic/multiview/multifrequency configuration; multistatic/single-view/multifrequency configuration; thin metallic cylinder localization; Electromagnetic fields; Electromagnetic measurements; Electromagnetic scattering; Ground penetrating radar; Image reconstruction; Inverse problems; Kirchhoff´s Law; Mathematical model; Optical scattering; Radar scattering; Experimental data; linear inverse scattering problem; singular value decomposition (SVD);
fLanguage
English
Journal_Title
Antennas and Propagation, IEEE Transactions on
Publisher
ieee
ISSN
0018-926X
Type
jour
DOI
10.1109/TAP.2008.927506
Filename
4589139
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