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Remote Sens. 2018, 10(9), 1417; https://doi.org/10.3390/rs10091417

Underground Object Classification for Urban Roads Using Instantaneous Phase Analysis of Ground-Penetrating Radar (GPR) Data

1
Composite Research Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Seongsan-gu, Changwon, Gyeongnam 51508, Korea
2
Advanced Railroad Vehicle Division, Korea Railroad Research Institute (KRRI), 176 Chelodo Bangmulgwan-ro, Uiwang, Gyeonggi 16105, Korea
3
School of Mechanical Engineering, Changwon National University, Changwon 641-773, Korea
4
Department of Architectural Engineering, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea
*
Author to whom correspondence should be addressed.
Received: 6 August 2018 / Revised: 31 August 2018 / Accepted: 4 September 2018 / Published: 6 September 2018
(This article belongs to the Special Issue Recent Progress in Ground Penetrating Radar Remote Sensing)
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Abstract

Ground-penetrating radar (GPR) has been widely used to detect subsurface objects, such as hidden cavities, buried pipes, and manholes, owing to its noncontact sensing, rapid scanning, and deeply penetrating remote-sensing capabilities. Currently, GPR data interpretation depends heavily on the experience of well-trained experts because different types of underground objects often generate similar GPR reflection features. Moreover, reflection visualizations that were obtained from field GPR data for urban roads are often weak and noisy. This study proposes a novel instantaneous phase analysis technique to address these issues. The proposed technique aims to enhance the visibility of underground objects and provide objective criteria for GPR data interpretation so that the objects can be automatically classified without expert intervention. The feasibility of the proposed technique is validated both numerically and experimentally. The field test utilizes rarely available GPR data for urban roads in Seoul, South Korea and demonstrates that the technique allows for successful visualization and classification of three different types of underground objects. View Full-Text
Keywords: ground-penetrating radar; underground object classification; urban road; sinkhole; signal processing; basis pursuit filter; phase analysis ground-penetrating radar; underground object classification; urban road; sinkhole; signal processing; basis pursuit filter; phase analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Park, B.; Kim, J.; Lee, J.; Kang, M.-S.; An, Y.-K. Underground Object Classification for Urban Roads Using Instantaneous Phase Analysis of Ground-Penetrating Radar (GPR) Data. Remote Sens. 2018, 10, 1417.

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