Forward-looking ground penetrating radar (FL-GPR) is an emerging modality that permits standoff sensing of targets buried at shallow depths in the ground. Most FL-GPR imagery is obtained using free-space approximation, neglecting the presence of the air-to-ground interface and assuming the propagation as occurring in a homogeneous dielectric medium. In this paper, we compare the performance of the approximate free-space tomographic imaging with that of a tomographic algorithm which accounts for the presence of the actual halfspace geometry. The half-space approach implements the spectral representation of the dyadic Green's function. Using numerical electromagnetic FL-GPR data, we investigate the impact of the free-space approximation on the image quality as well on the image-domain statistics of the targets and rough surface clutter.

Performance of free-space tomographic imaging approximation for shallow-buried target detection / Comite, D.; Ahmad, F.; Dogaru, T.. - 2017-:(2018), pp. 1-4. ( 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017 Curacao, NETH ANTILLE ) [10.1109/CAMSAP.2017.8313199].

Performance of free-space tomographic imaging approximation for shallow-buried target detection

Comite D.
;
2018

Abstract

Forward-looking ground penetrating radar (FL-GPR) is an emerging modality that permits standoff sensing of targets buried at shallow depths in the ground. Most FL-GPR imagery is obtained using free-space approximation, neglecting the presence of the air-to-ground interface and assuming the propagation as occurring in a homogeneous dielectric medium. In this paper, we compare the performance of the approximate free-space tomographic imaging with that of a tomographic algorithm which accounts for the presence of the actual halfspace geometry. The half-space approach implements the spectral representation of the dyadic Green's function. Using numerical electromagnetic FL-GPR data, we investigate the impact of the free-space approximation on the image quality as well on the image-domain statistics of the targets and rough surface clutter.
2018
7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017
forward-looking GPR; ground clutter; half-space Green's function; microwave imaging
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Performance of free-space tomographic imaging approximation for shallow-buried target detection / Comite, D.; Ahmad, F.; Dogaru, T.. - 2017-:(2018), pp. 1-4. ( 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2017 Curacao, NETH ANTILLE ) [10.1109/CAMSAP.2017.8313199].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1346314
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