2017
DOI: 10.1088/1742-2140/aa7303
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Wavelet analysis for ground penetrating radar applications: a case study

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Cited by 18 publications
(14 citation statements)
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“…In measurements taken with 25, 50, 250, and 500 MHz ground-coupled antennas to distinguish geological layers, wavelets Bioorthogonal 3.1 (for 25 and 50 MHz antennas), Bioorthogonal 3.5, 3 (250 MHz), and 7 (500 MHz) were used. Noise reduction was based on 5-level decomposition of the recorded GPR signal [ 33 ]. In [ 34 ], it was checked which wavelets are best suited for removing noise from the GPR signal from measurement on a flexible surface using a 1 GHz antenna.…”
Section: Wavelet Analysis Of Gpr Signalmentioning
confidence: 99%
“…In measurements taken with 25, 50, 250, and 500 MHz ground-coupled antennas to distinguish geological layers, wavelets Bioorthogonal 3.1 (for 25 and 50 MHz antennas), Bioorthogonal 3.5, 3 (250 MHz), and 7 (500 MHz) were used. Noise reduction was based on 5-level decomposition of the recorded GPR signal [ 33 ]. In [ 34 ], it was checked which wavelets are best suited for removing noise from the GPR signal from measurement on a flexible surface using a 1 GHz antenna.…”
Section: Wavelet Analysis Of Gpr Signalmentioning
confidence: 99%
“…This algorithm is simple to implement, but it is difficult to select appropriate thresholds when the SNR is low. Fourier transform and wavelet transform, which are widely used in images, are also used in GPR noise attenuation and direct wave eliminating [9], [10]. However, it takes a large amount of memory, so the computational efficiency is low [11].…”
Section: Introductionmentioning
confidence: 99%
“…Wavelet analysis is often applied in issues related to denoising of GPR radargrams [7,8]. Although there has been significant progress in time-frequency analyses [9], there is still a need to analyze and select the appropriate tools and methods for the extraction of true objects from images obtained with use of GPR [10].…”
Section: Introductionmentioning
confidence: 99%