scholarly journals A CLUTTER SUPPRESSION METHOD BASED ON IMPROVED PRINCIPAL COMPONENT SELECTION RULE FOR GROUND PENETRATING RADAR

2017 ◽  
Vol 53 ◽  
pp. 29-39 ◽  
Author(s):  
Jichao Zhu ◽  
Wei Xue ◽  
Xia Rong ◽  
Yunyun Yu
Keyword(s):  
Ground Penetrating Radar ◽  
Selection Rule ◽  
Principal Component ◽  
Clutter Suppression ◽  
Component Selection ◽  
Suppression Method ◽  
Ground Penetrating

A Clutter Suppression Algorithm for GPR Data Based on PCA Combining with Gradient Magnitude

2014 ◽  
Vol 644-650 ◽  
pp. 1662-1667 ◽  
Author(s):  
Qing Qing Lu ◽  
Jie Xin Pu ◽  
Xiao Hong Wang ◽  
Zhong Hua Liu
Keyword(s):  
Principal Component Analysis ◽  
Reinforced Concrete ◽  
Ground Penetrating Radar ◽  
Ground Surface ◽  
Principal Component ◽  
Clutter Suppression ◽  
Subtraction Method ◽  
Rc Structures ◽  
Gradient Magnitude ◽  
Ground Penetrating

Ground penetrating radar (GPR) is a powerful tool for detecting defects behind reinforced concrete (RC) structures. However, the received data from GPR includes a large number of clutters which are easy overwhelming the signal of target. In order to successfully extract the target signature, these clutters effects need to be eliminated. In this article, a clutter suppression algorithm based on Principal Component Analysis (PCA) combining with gradient magnitude is presented. PCA clutter suppression algorithm is applied to the data and removes most of the echoes from ground surface and portion of other clutters with weak energy. Then gradient magnitude clutter suppression is used to remove majority of the residue clutters. It is demonstrated from simulation that the proposed algorithm is able to significantly suppress the clutters and is superior to the PCA clutter suppression, magnitude clutter suppression and means subtraction method.

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.

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