Detection of shallow buried objects using an autoregressive model on the ground penetrating radar signal

2013 ◽  
Author(s):  
Daniel P. Nabelek ◽  
K. C. Ho
Keyword(s):  
Ground Penetrating Radar ◽  
Autoregressive Model ◽  
Radar Signal ◽  
Buried Objects ◽  
Ground Penetrating

Ground Penetrating Radar Radargram Filter using Singularity Expansion Method

2021 ◽  
Vol 35 (11) ◽  
pp. 1437-1438
Author(s):  
Eder Ruiz ◽  
Daniel Chaparro-Arce ◽  
John Pantoja ◽  
Felix Vega ◽  
Chaouki Kasmiv ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Expansion Method ◽  
Processing Technique ◽  
Sar Image ◽  
Metallic Material ◽  
Buried Objects ◽  
Ground Penetration Radar ◽  
Ground Penetrating

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.

Buried target signature extraction from ground-penetrating radar signal: measurements and simulations

2005 ◽  
Vol 4 (1) ◽  
pp. 31-38 ◽  
Author(s):  
Idesbald van den Bosch ◽  
Sébastien Lambot ◽  
Pascal Druyts ◽  
Isabelle Huynen ◽  
Marc Acheroy
Keyword(s):  
Ground Penetrating Radar ◽  
Radar Signal ◽  
Signature Extraction ◽  
Ground Penetrating

Study on Ground Penetrating Radar Signal Denoising Method Based on Surfacelet Transform and 3D Context Model

2014 ◽  
Vol 1010-1012 ◽  
pp. 1272-1275
Author(s):  
Dan Dan Liu ◽  
Zhi Qiu Yang ◽  
Chun Rui Tang
Keyword(s):  
Ground Penetrating Radar ◽  
Three Dimensional ◽  
Radar Signal ◽  
Signal Denoising ◽  
Context Model ◽  
Denoising Method ◽  
Subsurface Environment ◽  
Surface Singularities ◽  
Surfacelet Transform ◽  
Ground Penetrating

The ground penetrating radar and radar wave propagation in the subsurface environment is very complex. All kinds of noise and clutter interference is very serious, and detection echo data is a variety of with clutter. Therefore, the key techniques of data processing is to suppress clutter processing of ground penetrating radar record data. Surfacelet transform can efficiently capture and represent local surface singularities with different sizes. In order to improve the reliability of 3D ground penetrating radar detection results and accuracy, this paper presents a three-dimensional ground penetrating radar signal denoising method based on Surfacelet transform. Using Surfacelet transform and 3D context model for ground penetrating radar (GPR) analog signal to denoising, the noise in the case of low signal noise ratio (SNR) still can obtain a better result, and the simulations prove the effectiveness of the method.

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