Ground Penetrating Radar B-Scan Data Modeling and Clutter Suppression

2015 ◽  
Author(s):  
Zhiqiang Lin ◽  
Weidong Jiang
Keyword(s):  
Ground Penetrating Radar ◽  
Data Modeling ◽  
Clutter Suppression ◽  
Scan Data ◽  
Ground Penetrating

scholarly journals Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging

2020 ◽  
Vol 12 (5) ◽  
pp. 857 ◽  
Author(s):  
Davide Comite ◽  
Fauzia Ahmad ◽  
Traian Dogaru ◽  
Moeness Amin
Keyword(s):  
Rough Surface ◽  
Ground Penetrating Radar ◽  
Tomographic Reconstruction ◽  
Matched Filtering ◽  
Tomographic Image ◽  
Clutter Suppression ◽  
Coherence Factor ◽  
Ground Penetrating ◽  
Enhanced Imaging ◽  
Forward Looking

We present an enhanced imaging procedure for suppression of the rough surface clutter arising in forward-looking ground-penetrating radar (FL-GPR) applications. The procedure is based on a matched filtering formulation of microwave tomographic imaging, and employs coherence factor (CF) for clutter suppression. After tomographic reconstruction, the CF is first applied to generate a “coherence map” of the region in front of the FL-GPR system illuminated by the transmitting antennas. A pixel-by-pixel multiplication of the tomographic image with the coherence map is then performed to generate the clutter-suppressed image. The effectiveness of the CF approach is demonstrated both qualitatively and quantitatively using electromagnetic modeled data of metallic and plastic shallow-buried targets.

scholarly journals Sensitivity of the inverse problem solution related to detection of rebars buried in concrete by using GPR scanning

2018 ◽  
Vol 191 ◽  
pp. 00010 ◽  
Author(s):  
Zoubaida Mechbal ◽  
Abdellatif Khamlichi
Keyword(s):  
Inverse Problem ◽  
Perturbation Analysis ◽  
Ground Penetrating Radar ◽  
Problem Solution ◽  
Raw Data ◽  
Least Mean Squares ◽  
Identification Process ◽  
Inverse Problem Solution ◽  
Scan Data ◽  
Ground Penetrating

Ground Penetrating Radar is a device which is nowadays largely used in civil engineering applications. Considering a rebar buried in a concrete medium, this work addresses sensitivity of the inverse problem solution associated to identification of the object radius and its depth from B-scan data acquired by the GPR. The approach uses a closed form parameterisation of the hyperbola trace emerging in the radargram as function of the hyperbola apex coordinate along the direction of B-scan, the cover depth, the radius of the object and the relative permittivity of the medium. Estimation of the wave velocity, the hyperbola apex coordinates and the rebar radius was performed through solution of an appropriate nonlinear least mean squares problem. Perturbation analysis was then conducted by assuming that the hyperbola points coordinates, extracted from raw data of radargram, are randomly distributed according to Gaussian densities of probabilities. The effect of the amount of data was also analyzed. The method was implemented in Matlab environment. The obtained results have shown that identification process is extremely sensitive to noise affecting the B-scan raw data, but not to the number of points used in identification.

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