Sparse Wavelet Transform Based on Weight Vector Iteration with Minimum L1 Norm for Ground Penetrating Radar

Author(s):  
Renzhou Gui ◽  
Hao Liang ◽  
Juan Li ◽  
Mei Song Tong
Geophysics ◽  
2021 ◽  
pp. 1-74
Author(s):  
Lilong Zou ◽  
Kazutaka Kikuta ◽  
Amir M. Alani ◽  
Motoyuki Sato

The multi-layer nature of airport pavement structures is susceptible to the generation of voids at the bonding parts of the structure, which is also called interlayer debonding. Observations have shown that the thickness of the resulting voids is usually at the scale of millimeters, which makes it difficult to inspect. The efficient and accurate characteristics of ground penetrating radar (GPR) make it suitable for large area inspections of airport pavement. In this study, a multi-static GPR system was used to inspect the interlayer debonding of a large area of an airport pavement. A special antenna arrangement can obtain common mid-point (CMP) gathers during a common offset survey. The presence of interlayer debonding affects the phase of the reflection signals, and the phase disturbance can be quantified by wavelet transform. Therefore, an advanced approach that uses the average entropy of the wavelet transform parameters in CMP gathers to detect the interlayer debonding of airport pavement is proposed. The results demonstrate that the regions with high entropy correspond to the regions where tiny voids exist. The new approach introduced in this study was then evaluated by a field-base experiment at an airport taxiway model. The results show that the proposed approach can detect interlayer debonding of the pavement model accurately and efficiently. The on-site coring results confirm the performance of the proposed approach.


2019 ◽  
Vol 69 (1) ◽  
pp. 74-79
Author(s):  
Deniz Kumlu ◽  
Gökhan Karasakal ◽  
Nur Hüseyin Kaplan ◽  
Isin Erer

Target detection performance in ground-penetrating radar (GPR) deteriorates highly in the presence of clutter. Multi-scale (wavelet transform) or the recently proposed multi-scale and multi-directional decomposition based methods can efficiently remove the clutter, however they have high computational complexity. In this paper, we propose a new multi-scale method which requires only 1D fast subband decomposition of the rows of the GPR image. The resulting detail layers directly provide the clutter-free target component of the GPR image. The proposed method is compared to the state-of-art clutter removal methods both visually and quantitatively using a realistic simulated dataset which is constructed by the gprMax simulation software. The results show that the proposed 1D subband decomposition scheme approximates the classical 2D wavelet decomposition successfully and even presents a performance increase as well as a complexity decrease for fast decomposition methods based on lifting wavelet transform and a trous wavelet transform.


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