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Reconstruction hyperbola signature of underground object using GPR images for mapping applications.

Authors :
Masuan, N. A.
Ali, H.
Amran, T. S. Tengku
Zaidi, A. F. Ahmad
Kamarudin, K.
Ahmad, M. R.
Source :
AIP Conference Proceedings. 2024, Vol. 2898 Issue 1, p1-9. 9p.
Publication Year :
2024

Abstract

Ground penetrating radar has been acknowledged as an effective and efficient technique for non-destructive investigation for near-subsurface exploration that is based on the reflection receiver-transmitter of the antenna when hitting buried objects. An accurate interpretation of GPR data is greatly important in locating and mapping underground objects. Although GPR research has achieved remarkable success, the interpretation of GPR raw data highly depends on the reliance of user experts. Further, unexperienced GPR users are subject to error since the hyperbola signatures may resemble each other. Therefore, this work focuses on the development of a 3D reconstruction of the hyperbola signature of underground objects using GPR images for mapping applications. In this study, 3D reconstruction has been developed based on the Synthetic Aperture Focusing Technique, also known as SAFT. At the first stage, the raw input of GPR images was subjected to zero-time correction and background elimination. Next is the projection of each hyperbola signature by means of B-Scan images to create a 3D image. Then, the resultant 3D images were stacked together, and further 3D interpolation techniques were employed on the images. The experimental studies have been done on GPR data using a metal sphere as a sample. The findings of the study highlight that the SAFT method was able to reconstruct the 3D model of the hyperbola signature and exhibit the ability to provide clues about the location of the underground object through the representation of the voxel point of the images. Based on these results, the SAFT technique provides good insight into the 3D reconstruction of hyperbola signatures using GPR images in mapping applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2898
Issue :
1
Database :
Academic Search Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
175345799
Full Text :
https://doi.org/10.1063/5.0194241