This study proposes a low-complexity permittivity estimation for ground penetrating radar applications based on a contrast source inversion (CSI) approach, assuming multilayered ground media. The homogeneity assumption for each background layer is used to address the ill-posed condition while maintaining accuracy for permittivity reconstruction, significantly reducing the number of unknowns. Using an appropriate initial guess for each layer, the post-CSI approach also provides the dielectric profile of a buried object. The finite difference time domain numerical tests show that the proposed approach significantly enhances reconstruction accuracy for buried objects compared with the traditional CSI approach.
Yoshihiro YAMAUCHI
University of Electro-Communications
Shouhei KIDERA
University of Electro-Communications
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Yoshihiro YAMAUCHI, Shouhei KIDERA, "Contrast Source Inversion for Objects Buried into Multi-Layered Media for Subsurface Imaging Applications" in IEICE TRANSACTIONS on Electronics,
vol. E106-C, no. 7, pp. 427-431, July 2023, doi: 10.1587/transele.2022ECS6008.
Abstract: This study proposes a low-complexity permittivity estimation for ground penetrating radar applications based on a contrast source inversion (CSI) approach, assuming multilayered ground media. The homogeneity assumption for each background layer is used to address the ill-posed condition while maintaining accuracy for permittivity reconstruction, significantly reducing the number of unknowns. Using an appropriate initial guess for each layer, the post-CSI approach also provides the dielectric profile of a buried object. The finite difference time domain numerical tests show that the proposed approach significantly enhances reconstruction accuracy for buried objects compared with the traditional CSI approach.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/transele.2022ECS6008/_p
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@ARTICLE{e106-c_7_427,
author={Yoshihiro YAMAUCHI, Shouhei KIDERA, },
journal={IEICE TRANSACTIONS on Electronics},
title={Contrast Source Inversion for Objects Buried into Multi-Layered Media for Subsurface Imaging Applications},
year={2023},
volume={E106-C},
number={7},
pages={427-431},
abstract={This study proposes a low-complexity permittivity estimation for ground penetrating radar applications based on a contrast source inversion (CSI) approach, assuming multilayered ground media. The homogeneity assumption for each background layer is used to address the ill-posed condition while maintaining accuracy for permittivity reconstruction, significantly reducing the number of unknowns. Using an appropriate initial guess for each layer, the post-CSI approach also provides the dielectric profile of a buried object. The finite difference time domain numerical tests show that the proposed approach significantly enhances reconstruction accuracy for buried objects compared with the traditional CSI approach.},
keywords={},
doi={10.1587/transele.2022ECS6008},
ISSN={1745-1353},
month={July},}
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TY - JOUR
TI - Contrast Source Inversion for Objects Buried into Multi-Layered Media for Subsurface Imaging Applications
T2 - IEICE TRANSACTIONS on Electronics
SP - 427
EP - 431
AU - Yoshihiro YAMAUCHI
AU - Shouhei KIDERA
PY - 2023
DO - 10.1587/transele.2022ECS6008
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E106-C
IS - 7
JA - IEICE TRANSACTIONS on Electronics
Y1 - July 2023
AB - This study proposes a low-complexity permittivity estimation for ground penetrating radar applications based on a contrast source inversion (CSI) approach, assuming multilayered ground media. The homogeneity assumption for each background layer is used to address the ill-posed condition while maintaining accuracy for permittivity reconstruction, significantly reducing the number of unknowns. Using an appropriate initial guess for each layer, the post-CSI approach also provides the dielectric profile of a buried object. The finite difference time domain numerical tests show that the proposed approach significantly enhances reconstruction accuracy for buried objects compared with the traditional CSI approach.
ER -