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An Improved Hyperbolic Summation Imaging Algorithm for Detection of the Subsurface Targets

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An Improved Hyperbolic Summation Imaging Algorithm for Detection of the Subsurface Targets

In Ground penetrating Radar (GPR) imaging a single point target appears as a hyperbolic curve in the space-time image. In this study, for focusing hyperbolic curves in GPR images, we present an improved hyperbolic summation (HS) focusing technique based on cross-correlation receiving GPR data. First, the formulation of the proposed algorithm is presented. Second, for improve quality images result of HS imaging algorithm a weight factor is designed by analyzing the statistical character of receiving data for each point in region imaging. Third, this proposed algorithm applied on numerically and experimental GPR data and results shown that the proposed hyperbolic summation imaging algorithm superiority concentrate hyperbolic curves in GPR images and images result have a good quality and resolution. In order to quantitatively describe the imaging result for the effect of artifact suppression, focusing parameter is evaluated.

check Journal of Geophysics & Remote Sensing for more details.

 

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