• Journal of Korean Society of Disaster and Security
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• v.10 no.1
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• pp.61-66
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• 2017

It is very important to understand the electromagnetic characteristics of underground media in GPR (Ground Penetrating Radar) survey. Depending on the electrical characteristics of the underground medium, the energy of the electromagnetic wave becomes relatively small, and reflection from the interface may become difficult. In this study, electrical characteristics of sandy soils under various (loose and dense) conditions were analyzed. As a result, In dry sand is the dielectric constant increased as the relative density increased, and the dielectric constant and electrical conductivity increased as the moisture content of the sand increased.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.313-316
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• 2007

Ground-penetrating radar (GPR) is an effectiveness tool for imaging spatial distribution of hydrogeologic parameters. An artificial groundwater recharge test has been conducted in Nagaoka City in Japan, and time-lapse crosshole GPR data were collected to monitor infiltration processes in a vadose zone. Since radiowave velocities in a vadose zone are largely controlled by variations in water content, the increase in traveltimes is interpreted as an increase in saturation in the test zone. We use a finite-difference time-domain method in two-dimensional cylindrical coordinates to simulate field results. Numerical modeling successfully reproduces the major feature of velocity changes in the filtration process.

• Smart Structures and Systems
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• v.7 no.4
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• pp.319-328
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• 2011

In this study, the measurements of the dielectric constants of soil at 900 MHz and 1 GHz were made to relate those properties to the moisture content of the soil. This study's intention was to use the relationship between the dielectric constant and the moisture content to develop a landslide prediction system. By monitoring the change of the moisture content within the soil using ground penetrating radar (GPR) systems in the field, the possibility of a landslide is expected to be detected. To establish a database for the dielectric constants and the moisture content, the measurements of soil samples were made using both an open-ended dielectric coaxial probe and the GPR. Based on the measurement results, correlations between the GPR and reflector for each frequency at 900 MHz and 1 GHz were found for the dielectric constants and the moisture content. Finally, the mechanism of the measurement device to be implemented in the field is suggested.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.51-60
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• 2010

To determine subglacial topography and internal features of the Fourcade Glacier on King George Island in Antarctica, helicopter-borne and ground-towed ground-penetrating radar (GPR) data were recorded along four profiles in November 2006. Signature deconvolution, f-k migration velocity analysis, and finite-difference depth migration applied to the mixed-phase, single-channel, ground-towed data, were effective in increasing vertical resolution, obtaining the velocity function, and yielding clear depth images, respectively. For the helicopter-borne GPR, migration velocities were obtained as root-mean-squared velocities in a two-layer model of air and ice. The radar sections show rugged subglacial topography, englacial sliding surfaces, and localised scattering noise. The maximum depth to the basement is over 79m in the subglacial valley adjacent to the south-eastern slope of the divide ridge between Fourcade and Moczydlowski Glaciers. In the ground-towed profile, we interpret a complicated conduit above possible basal water and other isolated cavities, which are a few metres wide. Near the terminus, the GPR profiles image sliding surfaces, fractures, and faults that will contribute to the tidewater calving mechanism forming icebergs in Potter Cove.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2342-2344
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• 2005

초광대역 임펄스를 이용한 비파괴 지중 매설물 탐지용 지반 탐사 레이더(Ground penetrating image radar: GPR)를 개발하였다. 최대 탐사 깊이를 고려하여, 900 picosecond(ps) 상승 시간을 갖는 초광대역 임펄스를 설계하였고, 임펄스 발생기의 주파수 특성을 고려하여, 소형 평판형 다이폴 안테나가 설계되었다. 또한, 지중으로부터 반사되는 신호를 수신하기 위해서 고속의 A/D를 사용하였다. 측정은 송수신 안테나의 간격을 고정한 Bistatic 방식을 사용하였으며, 지중 매설물의 영상처리 판별을 위해 마이그레이션(migration) 기법을 사용하였다. 개발된 시스템은 금속 물체와 비금속 물체가 매설된 실증 시험장에서 시험되었고, 평면 해상도 및 깊이에 대한 해상도가 우수함을 보였다.

• Journal of the Korean Geotechnical Society
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• v.37 no.10
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• pp.65-76
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• 2021

There is a possibility of cavities occurring inside and behind the lining of an aged tunnel structure. In most cases, it is not easy to check the cavity because it exists in a place where visual inspection is impossible. Recently, attempts have been made to evaluate the condition of the tunnel lining and the backfill materials using non-destructive tests such as Ground Penetrating Radar, and various related model tests and numerical analysis studies have been conducted. In this study, the GPR signal characteristics for tunnel lining model testing were analyzed using gprMax software, which was compared with model test results. The numerical model applied to the model test reasonably simulated the electromagnetic wave signal according to the change of the material such as tunnel lining and internal cavity. Using the verified GPR model, B-scan data for the development of the GPR signal analysis technique were obtained, which can evaluate the thickness of the tunnel lining, the presence of the cavity, the effect of the waterproof membrane, and the frequency band.

• Journal of the Korea Concrete Institute
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• v.15 no.2
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• pp.209-216
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• 2003

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.285-294
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• 2020

This study investigated the use of Ground Penetrating Radar (GPR) over a two-decade period on public roads, focusing on the electromagnetic characteristics of the pavement dielectrics and attenuation. From the results, a typical range of characteristic value, influencing factors, and a correction method were suggested. The typical dielectrics of asphalt pavements were 4-7, as measured by an air-coupled 1 GHz GPR antenna. The dielectrics of concrete pavements were very large in the early age, but were drastically reduced with ageing. Ten years on, collection was in the range of 6-12. The dielectrics were proportional to the relative humidity (R.H.) of the atmosphere. The effects were reduced to one eighth with an overlay. Attenuation generally increased with thickness of the road layer, and also increased where there was damage. The GPR results could also vary depending on the weather conditions as well as on the characteristics of the GPR equipment, even at the same frequency. Therefore, GPR surveys should be performed on road surfaces without debris on a single, fine day. The reliability of the GPR analysis could be improved by cores and equipment calibration with other non-destructive test surveys.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.171-184
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• 2023

Machine learning (ML)-based cavity detection using a large amount of survey data obtained from vehicle-mounted ground penetrating radar (GPR) has been actively studied to identify underground cavities. However, only simple image processing techniques have been used for preprocessing the ML input, and many conventional seismic and GPR data processing techniques, which have been used for decades, have not been fully exploited. In this study, based on the idea that a cavity can be identified using diffraction, we applied ML-based diffraction separation to GPR data to increase the accuracy of cavity detection using the YOLO v5 model. The original ML-based seismic diffraction separation technique was modified, and the separated diffraction image was used as the input to train the cavity detection model. The performance of the proposed method was verified using public GPR data released by the Seoul Metropolitan Government. Underground cavities and objects were more accurately detected using separated diffraction images. In the future, the proposed method can be useful in various fields in which GPR surveys are used.