• Geophysics and Geophysical Exploration
• /
• v.20 no.2
• /
• pp.61-71
• /
• 2017

Recently, ground-penetrating radar (GPR) surveys have been actively carried out for precise subsurface void investigation because of the rapid increase of subsidence in urban areas. However, since the interpretation of GPR data was conducted based on the interpreter's subjective decision after applying only the basic data processing, it can result in reliability problems. In this research, to solve these problems, we analyzed the difference between the events generated from subsurface voids and those of strong diffraction sources such as the buried pipeline by applying the edge detection technique, which is one of image processing technologies. For the analysis, we applied the image processing technology to the GRP field data containing events generated from the cavity or buried pipeline. As a result, the main events by the subsurface void or diffraction source were effectively separated using the edge detection technique. In addition, since subsurface voids associated with the subsidence has a relatively wide scale, it is recorded as a gentle slope event unlike the event caused by the strong diffraction source recorded with a sharp slope. Therefore, the directional analysis of amplitude variation in the image enabled us to effectively separate the events by the subsurface void from those by the diffraction source. Interpretation based on these kinds of objective analysis can improve the reliability. Moreover, if suggested techniques are verified to various GPR field data sets, these approaches can contribute to semiautomatic interpretation of large amount of GPR data.

• Geophysics and Geophysical Exploration
• /
• v.24 no.3
• /
• pp.113-130
• /
• 2021

Recently, ground-penetrating radar (GPR) surveys have been actively employed to obtain a large amount of data on occurrences such as ground subsidence and road safety. However, considering the cost and time efficiency, more intuitive and accurate interpretation methods are required, as interpreting a whole survey data set is a cost-intensive process. For this purpose, GPR data can be subjected to attribute analysis, which allows quantitative interpretation. Among the seismic attributes that have been widely used in the field of exploration, complex trace analysis and similarity are the most suitable methods for analyzing GPR data. Further, recently proposed attributes such as edge detecting and texture attributes are also effective for GPR data analysis because of the advances in image processing. In this paper, as a reference for research on the attribute analysis of GPR data, we introduce the useful attributes for GPR data and describe their concepts. Further, we present an analysis of the interpretation methods based on the attribute analysis and past cases.

• Geophysics and Geophysical Exploration
• /
• v.8 no.4
• /
• pp.270-279
• /
• 2005

Under the research project supported by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), we have conducted the development of GPR systems for landmine detection. Until 2005, we have finished development of two prototype GPR systems, namely ALIS (Advanced Landmine Imaging System) and SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar). ALIS is a novel landmine detection sensor system combined with a metal detector and GPR. This is a hand-held equipment, which has a sensor position tracking system, and can visualize the sensor output in real time. In order to achieve the sensor tracking system, ALIS needs only one CCD camera attached on the sensor handle. The CCD image is superimposed with the GPR and metal detector signal, and the detection and identification of buried targets is quite easy and reliable. Field evaluation test of ALIS was conducted in December 2004 in Afghanistan, and we demonstrated that it can detect buried antipersonnel landmines, and can also discriminate metal fragments from landmines. SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar) is a machine mounted sensor system composed of B GPR and a metal detector. The GPR employs an array antenna for advanced signal processing for better subsurface imaging. SAR-GPR combined with synthetic aperture radar algorithm, can suppress clutter and can image buried objects in strongly inhomogeneous material. SAR-GPR is a stepped frequency radar system, whose RF component is a newly developed compact vector network analyzers. The size of the system is 30cm x 30cm x 30 cm, composed from six Vivaldi antennas and three vector network analyzers. The weight of the system is 17 kg, and it can be mounted on a robotic arm on a small unmanned vehicle. The field test of this system was carried out in March 2005 in Japan.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.2 no.4
• /
• pp.148-158
• /
• 1998

Determining the thickness if concrete lining and detecting of the cavity where is located behind tunnel lining plays an important role in the safety diagnosis of tunnel structure and the quality control. In this study, we made use of GPR and seismic method in order to find the cavity or flaw. Although GPR is very useful method in the concrete lining without rebar, it is difficult to detect the cavity in the reinforced concrete lining. We applied mini-seismic method to the reinforced concrete lining. The obtained seismic data was processed by means of seismic section in time domain and image section of power spectrum in frequency domain using Impact-Echo method as well. The proposed method can accurately show the location and depth of the cavity in the reinforced concrete lining.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.23 no.7
• /
• pp.66-71
• /
• 2019

In this paper, a study was conducted on the method of using GPR data to predict rebar thickness inside a facility. As shown in the cases of poor construction, such as the use of rebars below the domestic standard and the construction of reinforcement, information on rebar thickness can be found to be essential for precision safety diagnosis of structures. For this purpose, the B-scan data of GPR was obtained by gradually increasing the diameter of rebars by making specimen. Because the B-scan data of GPR is less visible, the data was converted into the heatmap image data through migration to increase the intuition of the data. In order to compare the results of application of commonly used B-scan data and heatmap data to CNN, this study extracted areas for rebars from B-scan and heatmap data respectively to build training and validation data, and applied CNN to the deployed data. As a result, better results were obtained for the heatmap data when compared with the B-scan data. This confirms that if GPR heatmap data are used, rebar thickness can be predicted with higher accuracy than when B-scan data is used, and the possibility of predicting rebar thickness inside a facility is verified.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.42 no.11
• /
• pp.101-106
• /
• 2005

A ground penetrating image radar (GPR) using an ultra wideband (UWB)impulse waveform is developed for non destructive detection of metallic pipelines buried under the ground. Dielectric constant of test field is measured and then a GPR system is designed for better detection up to 1 meter deep. By considering total path loss, volume of complete system, and resolution, upper and lower frequencies are chosen. First, a UWB impulse for the frequency bandwidth of the impulse is chosen with rising time less than 1 ns, and then compact planar UWB dipole antenna suitable for frequency bandwidth of a UWB impulse is designed. Also, to receive reflected signals, a digital storage oscilloscope is used. For measurement, a monostatic technique and a migration technique are used. For visualizing underground targets, simple image processing techniques of A-scan removal and B-scan average removal are applied. The prototype of the system is tested on a test field in wet clay soil and it is shown that the developed system has a good ability in detecting underground metal objects, even small targets of several centimeters.

• International Journal of Highway Engineering
• /
• v.18 no.6
• /
• pp.61-67
• /
• 2016

OBJECTIVES : The objective of this study is to detect road cavities using multi-channel 3D ground penetrating radar (GPR) tests owned by the Seoul Metropolitan Government. METHODS : Ground-penetrating radar tests were conducted on 204 road-cavity test sections, and the GPR signal patterns were analyzed to classify signal shape, amplitude, and phase change. RESULTS : The shapes of the GPR signals of road-cavity sections were circular or ellipsoidal in the plane image of the 3D GPR results. However, in the longitudinal or transverse direction, the signals showed mostly unsymmetrical (or symmetrical in some cases) parabolic shapes. The amplitude of the GPR signals reflected from road cavities was stronger than that from other media. No particular pattern of the amplitude was found because of nonuniform medium and utilities nearby. In many cases where road cavities extended to the bottom of the asphalt concrete layer, the signal phase was reversed. However, no reversed signal was found in subbase, subgrade, or deeper locations. CONCLUSIONS : For detecting road cavities, the results of the GPR signal-pattern analysis can be applied. In general, GPR signals on road cavity-sections had unsymmetrical hyperbolic shape, relatively stronger amplitude, and reversed phase. Owing to the uncertainties of underground materials, utilities, and road cavities, GPR signal interpretation was difficult. To perform quantitative analysis for road cavity detection, additional GPR tests and signal pattern analysis need to be conducted.

• Geophysics and Geophysical Exploration
• /
• v.12 no.1
• /
• pp.77-84
• /
• 2009

Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is applied to synthetic and field GPR data acquired over a buried pipe. The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a reference signal for pulse compression. For a pulse-compression filter, reference signal selection is an important issue, because as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is low. Analysis of the results obtained from simulated and field GPR data indicates a significant improvement in the GPR image, good discrimination between the target reflection and the ground surface reflection, and better performance with reliable separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.

• Geophysics and Geophysical Exploration
• /
• v.12 no.1
• /
• pp.69-76
• /
• 2009

We report an implementation of the Ground Penetrating Radar (GPR) survey at a site that corresponds to a ruined castle. The objective of the survey was to characterise buried archaeological structures such as walls and tiles in Van Khan Tooril's Ruin, Mongolia, by 2D and 3D GPR techniques. GPR datasets were acquired in an area 10mby 9 m, with 10 cm line spacing. Two datasets were collected, using GPR with 500MHz and 800MHz frequency antennas. In this paper, we report the use of instantaneous parameters to detect archaeological targets such as tile, brick, and masonry by polarimetric GPR. Radar polarimetry is an advanced technology for extraction of target scattering characteristics. It gives us much more information about the size, shape, orientation, and surface condition of radar targets. We focused our interpretation on the strongest reflections. The image is enhanced by the use of instantaneous parameters. Judging by the shape and the width of the reflections, it is clear that moderate to high intensity response in instantaneous amplitude corresponds to brick and tiles. The instantaneous phase map gave information about the location of the targets, which appeared as discontinuities in the signal. In order to increase our ability to interpret these archaeological targets, we compared the GPR datasets acquired in two orthogonal survey directions. A good correlation is observed for the alignments of reflections when we compare the two datasets. However, more reflections appear in the north-south survey direction than in the west-east direction. This is due to the electric field orientation, which is in the horizontal plane for north-south survey directions and the horizontally polarised component of the backscattered high energy is recorded.

• Journal of the Society of Disaster Information
• /
• v.16 no.1
• /
• pp.60-69
• /
• 2020

Purpose: Cavity growth process monitoring is to periodically monitor changes in common size and topography for general and observational grades to predict the rate of common growth. The purpose of this study is to establish a systematic cavity management plan by evaluating the general and observational class community in a non-destructive method. Method: Using GPR exploration equipment, the acquired surface image and the surrounding status image are analyzed in the GPR probe radargram in depth, profile, and cross section of the location. The exact location is selected using the distance and surrounding markings shown on the road surface of the initial detection cavity, and the test cavity is analyzed by calling the radar at the corresponding location. Result: As a result of monitoring tests conducted at a cavity 30 sites of general and observation grade, nine sites have been recovered. Changes in scale were seen in 21 cavity locations, and changes in size and grade occurred in 13 locations. Conclusion: The under road cavity is caused by various causes such as damage to the burial site, poor construction, soil leakage caused by groundwater leakage, waste and ground vibration. Among them, indirect factors could infer the effects of groundwater and localized rainfall.