Comparative analysis of clutter suppression techniques for landmine detection using ground-penetrating radar

2011 ◽  
Author(s):  
Ahmet Burak Yoldemir ◽  
Rıdvan Gürcan ◽  
Gülay Büyükaksoy Kaplan ◽  
Mehmet Sezgin
Keyword(s):  
Comparative Analysis ◽  
Ground Penetrating Radar ◽  
Landmine Detection ◽  
Clutter Suppression ◽  
Ground Penetrating

scholarly journals GPR Signal Processing with Geography Adaptive Scanning using Vector Radar for Antipersonal Landmine Detection

10.5772/5696 ◽  
2007 ◽  
Vol 4 (2) ◽  
pp. 22 ◽  
Author(s):  
Toshio Fukuda ◽  
Yasuhisa Hasegawa ◽  
Yasuhiro Kawai ◽  
Shinsuke Sato ◽  
Zakarya Zyada ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Ground Surface ◽  
Landmine Detection ◽  
Image Objects ◽  
Kirchhoff Migration ◽  
Surface Image ◽  
Buried Object ◽  
Ground Penetrating ◽  
The Relationship ◽  
Object Imaging

Ground Penetrating Radar (GPR) is a promising sensor for landmine detection, however there are two major problems to overcome. One is the rough ground surface. The other problem is the distance between the antennas of GPR. It remains irremovable clutters on a sub-surface image output from GPR by first problem. Geography adaptive scanning is useful to image objects beneath rough ground surface. Second problem makes larger the nonlinearity of the relationship between the time for propagation and the depth of a buried object, imaging the small objects such as an antipersonnel landmine closer to the antennas. In this paper, we modify Kirchhoff migration so as to account for not only the variation of position of the sensor head, but also the antennas alignment of the vector radar. The validity of this method is discussed through application to the signals acquired in experiments.

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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