Published

2024-09-19

Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters

Separación por difracción de información recolectada con georradar a través de la aplicación de filtros de máscara

DOI:

https://doi.org/10.15446/esrj.v28n2.112936

Keywords:

Ground Penetrating Radar (GPR), Geological Disease Survey, GPR Signal Denoising, Diffraction Separation, Masking Filter (en)
Georradar, detección de problemas geológicos, eliminación de ruido de señal en georradar, difracción (es)

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Authors

  • Zhijun Li Civil Engineering, Southwest Jiaotong University, Chengdu 611756, China
  • Hui Sun Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China
  • Ruoge Xu Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China
  • Rui Chen Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China
  • Hongyong Ren Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China
  • Chenglang Wang Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China
  • Fuliu Gao Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China.
  • Mingnian Wang Civil Engineering, Southwest Jiaotong University, Chengdu, China

Ground penetrating radar is a high-resolution, efficient, non-destructive geophysical detection method. It is widely used in various application scenarios such as tunnel geological prediction and road maintenance. Ground penetrating radar data contains a variety of valid signals as well as noise. The diffracted waves of ground penetrating radar contain high-resolution small target imaging information. A critical challenge in GPR applications is how to extract diffracted waves from the wave fields. We provide a strategy to achieve this goal by applying the masking filters. Considering the complexity of the ground penetrating radar wave field and the weak energy of the diffracted waves, the median filter is first employed to suppress the linear reflections and then the f-k filter and filter are implemented to further increase the proportion of diffractions in the wave fields. Three numerical experiments are employed to test the diffraction-separation method.

El georradar es un método de detección geofísica de alta resolución, eficiente, y no destructivo. Se usa ampliamente en varios escenarios, como en la predicción de túneles geológicos y en el mantenimiento de carreteras. La información del georradar contiene una variedad de señales válidas pero también ruido. Las ondas difractadas del georradar contienen información detallada de pequeños objetivos en alta resolución. Uno de los principales problemas en las aplicaciones de georradar es el cómo extraer las ondas difractadas a partir de los campos de ondas. En este artículo se presenta una estrategia para lograr este objetivo a través de aplicar filtros de máscara. Al partir de la complejidad de la onda de campo del georradar y la señal débil de las ondas difractadas, el filtro mediano se usa inicialmente para suprimir las reflexiones lineales, y luego se implementan los filtros f-k y para incrementar la proporción de difracción en los campos de ondas. Se emplearon además tres experimentos numéricos para evaluar el método de separación por difracción.

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How to Cite

APA

Li, Z., Sun, H., Xu, R., Chen, R., Ren, H., Wang, C., Gao, F. & Wang, M. (2024). Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters. Earth Sciences Research Journal, 28(2), 175–181. https://doi.org/10.15446/esrj.v28n2.112936

ACM

[1]
Li, Z., Sun, H., Xu, R., Chen, R., Ren, H., Wang, C., Gao, F. and Wang, M. 2024. Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters. Earth Sciences Research Journal. 28, 2 (Sep. 2024), 175–181. DOI:https://doi.org/10.15446/esrj.v28n2.112936.

ACS

(1)
Li, Z.; Sun, H.; Xu, R.; Chen, R.; Ren, H.; Wang, C.; Gao, F.; Wang, M. Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters. Earth sci. res. j. 2024, 28, 175-181.

ABNT

LI, Z.; SUN, H.; XU, R.; CHEN, R.; REN, H.; WANG, C.; GAO, F.; WANG, M. Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters. Earth Sciences Research Journal, [S. l.], v. 28, n. 2, p. 175–181, 2024. DOI: 10.15446/esrj.v28n2.112936. Disponível em: https://revistas.unal.edu.co/index.php/esrj/article/view/112936. Acesso em: 27 dec. 2025.

Chicago

Li, Zhijun, Hui Sun, Ruoge Xu, Rui Chen, Hongyong Ren, Chenglang Wang, Fuliu Gao, and Mingnian Wang. 2024. “Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters”. Earth Sciences Research Journal 28 (2):175-81. https://doi.org/10.15446/esrj.v28n2.112936.

Harvard

Li, Z., Sun, H., Xu, R., Chen, R., Ren, H., Wang, C., Gao, F. and Wang, M. (2024) “Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters”, Earth Sciences Research Journal, 28(2), pp. 175–181. doi: 10.15446/esrj.v28n2.112936.

IEEE

[1]
Z. Li, “Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters”, Earth sci. res. j., vol. 28, no. 2, pp. 175–181, Sep. 2024.

MLA

Li, Z., H. Sun, R. Xu, R. Chen, H. Ren, C. Wang, F. Gao, and M. Wang. “Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters”. Earth Sciences Research Journal, vol. 28, no. 2, Sept. 2024, pp. 175-81, doi:10.15446/esrj.v28n2.112936.

Turabian

Li, Zhijun, Hui Sun, Ruoge Xu, Rui Chen, Hongyong Ren, Chenglang Wang, Fuliu Gao, and Mingnian Wang. “Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters”. Earth Sciences Research Journal 28, no. 2 (September 19, 2024): 175–181. Accessed December 27, 2025. https://revistas.unal.edu.co/index.php/esrj/article/view/112936.

Vancouver

1.
Li Z, Sun H, Xu R, Chen R, Ren H, Wang C, Gao F, Wang M. Diffraction Separation for the Ground Penetrating Radar Data by Masking Filters. Earth sci. res. j. [Internet]. 2024 Sep. 19 [cited 2025 Dec. 27];28(2):175-81. Available from: https://revistas.unal.edu.co/index.php/esrj/article/view/112936

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