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The continuous wavelet transform in processing data of high frequency electromagnetic prospecting

Tin Quoc Chanh Duong 1, *
Dau Hieu Duong 1
Van Thanh Nguyen 2
Thuan Van Nguyen 2
  1. Can Tho University
  2. University of Science, VNU-HCM
Correspondence to: Tin Quoc Chanh Duong, Can Tho University. Email: pvphuc@vnuhcm.edu.vn.
Volume & Issue: Vol. 19 No. 2 (2016) | Page No.: 81-93 | DOI: 10.32508/stdj.v19i2.806
Published: 2016-06-30

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Copyright The Author(s) 2023. This article is published with open access by Vietnam National University, Ho Chi Minh city, Vietnam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

Ground Penetrating Radar (GPR), a high frequency electromagnetic prospecting method (10 to 3000 MHz) has been rapidly developed in recent decades. With many advantages such as non-destructive, fast data collection, high precision and resolution, this method is a useful means to detect underground targets. It is currently used in the research of studying the shallow structure for examples: forecast landslide, subsidence, mapping urban underground works, traffic, construction, archaeology and other various fields of engineering, GPR data processing is becoming increasingly urgent. Wavelet transform is one of the new signal analysis tools, plays a vital role in numerous domains like image processing, graphics, data compression, gravitational, electromagnetic and geomagnetic data processing, GPR and some others. In this study, we used the continuous wavelet transform (CWT) and multiscale edge detection (MED) with the wavelet functions which were appropriately selected to determine underground targets. The accuracy of this technique was tested on some theoretical models before being applied on experimental data. The obtained results showed that this was a feasible method that could be used to detect the size and position of the anomaly objects.

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