scholarly journals Feature Extraction based on Empirical Mode Decomposition for Shapes Recognition of Buried Objects by Ground Penetrating Radar

2021 ◽  
Vol 1878 (1) ◽  
pp. 012022
Author(s):  
Hasimah Ali ◽  
Mohd Shuhanaz Zanar Azalan ◽  
Ahmad Firdaus Ahmad Zaidi ◽  
Tengku Sarah Tengku Amran ◽  
Mohamad Ridzuan Ahmad ◽  
...  
Forests ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 230 ◽  
Author(s):  
Xi Wu ◽  
Christopher Adam Senalik ◽  
James Wacker ◽  
Xiping Wang ◽  
Guanghui Li

An object detection method of ground-penetrating radar (GPR) signals using empirical mode decomposition (EMD) and dynamic time warping (DTW) is proposed in this study. Two groups of timber specimens were examined. The first group comprised of Douglas fir (Pseudotsuga menziesii) timber sections prepared in the laboratory with inserts of known internal characteristics. The second group comprised of timber girders salvaged from the timber bridges on historic Route 66 over 80 years. A GSSI Subsurface Interface Radar (SIR) System 4000 with a 2 GHz palm antenna was used to scan these two groups of specimens. GPR sensed differences in dielectric constants (DC) along the scan path caused by the presence of water, metal, or air within the wood. This study focuses on the feature identification and defect classification. The results show that the processing methods were efficient for the illustration of GPR information.


2021 ◽  
Vol 1997 (1) ◽  
pp. 012018
Author(s):  
H Ali ◽  
A F Ahmad Zaidi ◽  
W K Wan Ahmad ◽  
M S Zanar Azalan ◽  
T S Tengku Amran ◽  
...  

2021 ◽  
Vol 35 (11) ◽  
pp. 1437-1438
Author(s):  
Eder Ruiz ◽  
Daniel Chaparro-Arce ◽  
John Pantoja ◽  
Felix Vega ◽  
Chaouki Kasmiv ◽  
...  

In this paper, the singularity expansion method (SEM) is used to improve the signal-to-clutter ratio of radargrams obtained with a ground penetration radar (GPR). SEM allows to select the poles of the GPR signals corresponding to unwanted signals, clutter, and also reflections of specific buried objects. A highly reflective metallic material was used to assess the use of SEM as a tool to eliminate unwanted reflections and signals produced by a GPR. Selected clutter poles are eliminated from each frame of the SAR image in order to keep only desired poles for analysis. Finally, the reconstructed radargram obtained applying SEM is compared with the image obtained using a well-known processing technique. Results show that the proposed technique can be used to straightforwardly remove undesired signals measured with GPRs.


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