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GPR Data Interpretation using Continuous Wavelet Transform:A Different Approach


Affiliations
1 Department of Applied Geophysics, Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, India
 

The objective of this communication is to establish a new technique for GPR data interpretation using continuous wavelet transform (CWT) approach. In the present study, we have adapted the CWT technique to detect the edges or abrupt changes in the signal. For validation of the proposed technique, we have acquired data over a known tunnel in point mode and time mode using two antennas of two different frequencies (40 MHz and 80 MHz). The tunnel is already known in the area, however information of overburden depth and extension of the tunnel was not properly known. Initially, GPR data have been processed using standard processing (RADAN 7.0) software and the tunnel has been delineated by the two small peaks in the signal. Sometimes, it becomes tough to interpret the small changes or discontinuities in the reflected GPR signal processed by the available standard software. Further, CWT has been performed on a wavelet around the same time depth at which tunnel has been detected based on the standard processing of the GPR data. The tunnel has been prominently delineated by the high wavelet coefficient values. A comparative analysis for width and depth estimation using GPR data and CWT technique has been carried out. While implementing CWT, it is essential to choose the suitable mother wavelet for high-resolution scalogram plot. Mother wavelet for our study area has been selected based on the maximum normalized mean power value of wavelet coefficients. We discuss an approach for tunnel detection and provide an efficient procedure to improve detection performance.

Keywords

CWT, Dielectric, GPR, Mother Wavelet, Scalogram, Tunnel.
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  • GPR Data Interpretation using Continuous Wavelet Transform:A Different Approach

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Authors

Sarvesh Kumar
Department of Applied Geophysics, Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, India
Sanjit Kumar Pal
Department of Applied Geophysics, Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, India
Soma Rani
Department of Applied Geophysics, Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, India
Saurabh
Department of Applied Geophysics, Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, India

Abstract


The objective of this communication is to establish a new technique for GPR data interpretation using continuous wavelet transform (CWT) approach. In the present study, we have adapted the CWT technique to detect the edges or abrupt changes in the signal. For validation of the proposed technique, we have acquired data over a known tunnel in point mode and time mode using two antennas of two different frequencies (40 MHz and 80 MHz). The tunnel is already known in the area, however information of overburden depth and extension of the tunnel was not properly known. Initially, GPR data have been processed using standard processing (RADAN 7.0) software and the tunnel has been delineated by the two small peaks in the signal. Sometimes, it becomes tough to interpret the small changes or discontinuities in the reflected GPR signal processed by the available standard software. Further, CWT has been performed on a wavelet around the same time depth at which tunnel has been detected based on the standard processing of the GPR data. The tunnel has been prominently delineated by the high wavelet coefficient values. A comparative analysis for width and depth estimation using GPR data and CWT technique has been carried out. While implementing CWT, it is essential to choose the suitable mother wavelet for high-resolution scalogram plot. Mother wavelet for our study area has been selected based on the maximum normalized mean power value of wavelet coefficients. We discuss an approach for tunnel detection and provide an efficient procedure to improve detection performance.

Keywords


CWT, Dielectric, GPR, Mother Wavelet, Scalogram, Tunnel.

References





DOI: https://doi.org/10.18520/cs%2Fv118%2Fi7%2F1104-1111