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This paper proposes the implementation of and experimentation with GPR for real-time automatic detection of buried IEDs. GPR, consisting of hardware and software, was implemented. A UWB antenna was designed and implemented, particularly for the operation of the GPR. The experiments were conducted in order to demonstrate the real-time automatic detection of buried IEDs using GPR with an R-CNN algorithm. In the experiments, the GPR was mounted on a pickup truck and a maintenance train in order to find the IEDs buried under a road and a railway, respectively. B-scan images were collected using the implemented GPR. R-CNN-based detection for the hyperbolic pattern, which indicates the buried IED, was performed along with pre-processing, for example, using zero offset removal, and background removal and filtering. Experimental results in terms of detecting the hyperbolic pattern in B-scan images were shown and verified that the proposed GPR system is superior to the conventional one using region analysis processing-based detection. Results also showed that pre-processing is required in order to improve and/or clean the hyperbolic pattern before detection. The GPR can automatically detect IEDs buried under roads and railways in real time by detecting the hyperbolic pattern appearing in the collected B-scan image.

In most Latin American countries, there are significant numbers of missing people and forced disappearances, over 120,000 in Colombia alone. Successful detection of shallow buried human remains by forensic search teams is difficult in varying terrain and climates. Previous research has created controlled simulated clandestine graves of murder victims to optimize search techniques and methodologies. This paper reports on a study on controlled test site results over four simulated dismembered victims' clandestine graves as this is sadly a common scenario encountered in Latin America. Multispectral images were collected once post-burial, electrical resistivity surveys were collected 4 times, and ground penetrating radar (GPR) surveys were collected three times up to the end of the 371 day survey monitoring period. After data processing, results showed that the multispectral data set could detect the simulated clandestine and control graves, with electrical resistivity imaging relative high resistances over some of the simulated graves but not over the empty control graves. GPR results showed good imaging on the Day 8 surveys, medium imaging on the Day 294 surveys, and medium to good imaging on the Day 371 surveys. Study implications suggest that, while clandestine graves of dismembered homicide victims would likely result in smaller-sized graves when compared to graves containing intact bodies, these graves can still potentially be detected using remote sensing and geophysical methods., (© 2021 American Academy of Forensic Sciences.)

In the past 20 years, many studies have been performed on ballast layer inspection and condition evaluation with ground penetrating radar (GPR). GPR is a non-destructive means that can reflect the ballast layer condition (fouling, moisture) by analysing the received signal variation. Even though GPR detection/inspection for ballast layers has become mature, some challenges still need to be stressed and solved, e.g., GPR indicator (for reflecting fouling level) development, quantitative evaluation for ballast fouling levels under diverse field conditions, rapid GPR inspection, and combining analysis of GPR results with other data (e.g., track stiffness, rail acceleration, etc.). Therefore, this paper summarised earlier studies on GPR application for ballast layer condition evaluation. How the GPR was used in the earlier studies was classified and discussed. In addition, how to correlate GPR results with ballast fouling level was also examined. Based on the summary, future developments can be seen, which is helpful for supplementing standards of ballast layer evaluation and maintenance.

Understanding linkages between heterogeneous soil structures and non-uniform flow is fundamental for interpreting infiltration processes and improving hydrological simulations. Here, we utilized ground-penetrating radar (GPR) as a non-invasive technique to investigate those linkages and to complement current traditional methods that are labor-intensive, invasive, and non-repeatable. We combined time-lapse GPR surveys with different types of infiltration experiments to create three-dimensional (3D) diagrams of the wetting dynamics. We carried out the GPR surveys and validated them with in situ observations, independent measurements and field excavations at two experimental sites. Those sites were selected to represent different mechanisms that generate non-uniform flow: (1) preferential water infiltration initiated by tree trunk and root systems; and (2) lateral subsurface flow due to soil layering. Results revealed links between different types of soil heterogeneity and non-uniform flow. The first experimental site provided evidence of root-induced preferential flow paths along coarse roots, emphasizing the important role of coarse roots in facilitating preferential water movement through the subsurface. The second experimental site showed that water infiltrated through the restrictive layer mainly following the plant root system. The presented approach offers a non-invasive, repeatable and accurate way to detect non-uniform flow., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Non-destructive tests are strongly required in engineering applications for monitoring civil structures. The use of compared and integrated innovative approaches based on geophysical methodologies represents an effective tool for the characterization and monitoring of reinforced concrete (RC) structures. Therefore, the main aim of the work was to improve the knowledge on the potentiality and limitations of the Ground Penetrating Radar (GPR) and the Electrical Resistivity Tomography (ERT) with electrodes disposed both on the surface and in the boreholes. The work approach was adopted on an analog model of a reinforced concrete frame built ad hoc at the Hydrogeosite Laboratory (CNR-IMAA), where simulated experiments on full-size physical models are defined. Results show the ability of an accurate use of GPR to reconstruct the rebar dispositions and detect in detail possible constructive defects, both highlighting the lack of reinforcements into the nodes and providing useful information about the safety assessment of the realized structure. The results of the ERT method defined the necessity to develop ad-hoc electrical resistivity methods to support the characterization and monitoring of buried foundation structures for civil engineering applications. Finally, the paper introduces a new approach based on the use of cross-hole ERTs (CHERTs) for the engineering structure monitoring, able to reduce the uncertainties usually affecting the indirect results.

In civil structures and infrastructure, assessing true performance and characterizing unusual structural behaviors can help avoid severe structural problems. To further refine or validate the conclusions from structural health monitoring (SHM) analyses, nondestructive evaluation or techniques (NDE or NDT) can be applied in conjunction with SHM approaches. Ground penetrating radar (GPR) is an NDT that has been used to investigate defects and internal features in concrete structures, but is not commonly used to assess mechanical properties for the purposes of SHM. As a preliminary investigation of the effectiveness of attribute analysis techniques, a GPR survey was conducted on Streicker Bridge (a pedestrian bridge on Princeton University campus with embedded fiber-optic strain and temperature sensors). The bridge was constructed in two phases, where different curing conditions produced different material properties (compressive strength of 51 MPa and 59 MPa). Both standard processing techniques and attribute analysis techniques were employed to interpret GPR reflections in each phase of construction to identify construction elements and to compare the attribute signatures of different strength concretes.Though this study presents primarily relative differences, the sensitivity of these attributes to material property differences is confirmed. This validates SHM studies of the bridge and indicates the potential of the attribute analysis method for material characterization, especially as a compliment to other SHM and NDE techniques.

In forensic geophysical research, using controlled experiments assists forensic search practitioners in identifying optimal technique(s) and equipment configuration(s) in different burial scenarios. The objective of the research is to observe the geophysical response to different types of buried wrappings, taking into consideration the influence that the presence or absence of a decomposing body (pig carcass) in a lateritic soil in central-western Brazil can have. In this article, the GPR results are presented after a 15day burial period during the rainy season, and the results of Electrical resistivity tomography (ERT) after a burial period of 6 months during the dry season. The controlled site was built in the research area of the University of Brasília, in a region with soil, typical of the Brazilian savannah. 14 simulated clandestine graves of murder victims were constructed, in which seven pig carcasses were wrapped or covered by: soil (backfill), a plastic bag, a bed sheet, cement block, construction debris, a wooden coffin and hydrated lime, respectively a further seven burials, presenting only the wrappings acted as comparison (control burial). During the GPR survey a 400MHz frequency antenna was used. The resistivity surveys were carried out before and after the burial of the targets with dipole-dipole and Wenner-Schlumberger array configurations, with different spacing of electrodes (1.00 and 0.50m). The comparison between the various scenarios with and without pig carcasses revealed that good reflection events occurred mainly due to the wrappings and that pig carcasses attenuated the GPR signal. Electrical resistivity results showed that the Wenner-Schlumberger array presents a better resolution of the lateral boundaries of the burials, and the dipole-dipole array presents a better sensitivity to heterogeneity of the buried materials. The burials with the pig carcasses wrapped in the various materials presented better resistivity contrasts as opposed to the control burials., (Copyright © 2018 Elsevier B.V. All rights reserved.)

An estimated 500,000 people died from all causes during the Spanish Civil War between 1936 and 1939, with a further 135,000 killed after the war ended. There are currently over 2000 known mass burial locations throughout Spain but many more are unknown. This study details the successful search for an unmarked mass grave in mountainous terrain in the Asturias region of Northern Spain. Two approximate locations were known due to eyewitness accounts. A phased site investigation approach was undertaken, which included Ground Penetrating Radar. Results showed a clear geophysical anomaly on 2D GPR profiles. The identified area was subsequently intrusively investigated by forensic archaeologists and human remains were successfully discovered. Careful and sensitive investigations are essential in these approaches where living relatives are involved., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

In most Latin American countries there are significant numbers of missing people and forced disappearances, 68,000 alone currently in Colombia. Successful detection of shallow buried human remains by forensic search teams is difficult in varying terrain and climates. This research has created three simulated clandestine burial styles at two different depths commonly encountered in Latin America to gain knowledge of optimum forensic geophysics detection techniques. Repeated monitoring of the graves post-burial was undertaken by ground penetrating radar. Radar survey 2D profile results show reasonable detection of ½ clothed pig cadavers up to 19 weeks of burial, with decreasing confidence after this time. Simulated burials using skeletonized human remains were not able to be imaged after 19 weeks of burial, with beheaded and burnt human remains not being able to be detected throughout the survey period. Horizontal radar time slices showed good early results up to 19 weeks of burial as more area was covered and bi-directional surveys were collected, but these decreased in amplitude over time. Deeper burials were all harder to image than shallower ones. Analysis of excavated soil found soil moisture content almost double compared to those reported from temperate climate studies. Vegetation variations over the simulated graves were also noted which would provide promising indicators for grave detection., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

This paper investigates the use of ground-penetrating radar (GPR) technology for detecting shallow buried objects, utilizing an air-coupled stepped frequency continuous wave (SFCW) radar system that operates within a 2 GHz bandwidth starting at 500 MHz. Different GPR data acquisition methods for air-coupled systems are compared, specifically down-looking, side-looking, and circular acquisition strategies, employing the back projection algorithm to provide focusing of the acquired GPR data. Experimental results showed that the GPR can penetrate up to 0.6 m below the surface in a down-looking mode. The developed radar and the back projection focusing algorithm were used to acquire data in the side-looking and circular mode, providing focused images with a resolution of 0.1 m and detecting subsurface objects up to 0.3 m below the surface. The proposed approach transforms B-scans of the GPR-based data into 2D images. The provided approach has significant potential for advancing shallow object detection capabilities by transforming hyperbola-based features into point-like features. [ABSTRACT FROM AUTHOR]

Estimates of radar attenuation in the shallow Martian subsurface are retrieved from RIMFAX soundings along the Perseverance rover traverse. Specifically, analyzed data is from the Hawksbill Gap area during the rover's first drives onto the Jezero Western Fan Front. The centroid frequency‐shift method is employed to quantify attenuation in terms of the constant‐Q approximation. Results are then compared with the amplitude decay method, which—in order to calculate attenuation—requires propagation velocities retrieved from radargram analysis. By verifying that results from two separate analyses are consistent, we ensure that quantified radar properties are well constrained. First estimate of constant‐Q is 78.8 ± 11.6. For a subsurface propagation velocity of 0.113 m/ns, that equals an attenuation of −2.1 ± 0.4 dB/m at the RIMFAX 675 MHz center frequency. Results are consistent with dry sedimentary rocks, and are distinguishable from the magmatic lithologies on Jezero Crater Floor. Plain Language Summary: This study presents first estimates of radar attenuation at the Jezero Western Fan Front. Measurements were made with the RIMFAX payload instrument on the Mars 2020 Perseverance rover mission, acquired along the rover drive path. Results indicate low signal losses in the subsurface that are consistent with dry sedimentary rocks, as observed on the surface by other payload instruments. Maximum imaging depths increase compared to imaging over magmatic lithologies on Jezero Crater Floor. By using separate methods of analysis (the centroid frequency‐shift method and the amplitude decay method), we reliably quantify attenuation and maximum penetration depths at the Western Fan Front, and observe differences to the Crater Floor lithologies. Key Points: The first estimate of radar attenuation at the Jezero Western Fan Front is on average −2.1 dB/mFor an average propagation velocity of 0.113 m/ns, returned power and time‐frequency analyses yield similar resultsRadar properties are consistent with dry sedimentary rocks and are distinguishable from the magmatic lithologies on Jezero Crater Floor [ABSTRACT FROM AUTHOR]

Featured Application: Object detection method based on three-dimensional GPR data of railroad tracks using AI, trained solely on simulation data. Ground-penetrating radar (GPR) is a non-invasive technology that uses electromagnetic pulses for subsurface exploration. In the railroad sector, it is crucial to assessing soil layers and infrastructure, offering insights into soil stratification and geological features and aiding in identifying subsurface hazards. However, the automation of radargram analysis is impeded by the lack of ground truth—accurate real-world data used to validate machine learning models—thus affecting the deployment of advanced algorithms. This study focuses on generating high-quality simulated data to address the shortage of real-world data in the context of object detection along railroad tracks and presents a fully automated pipeline that includes data generation, algorithm training, and validation using real-world data. By doing so, it paves the way for significantly easing the future task of object detection algorithms in the railway sector. A simulation environment, including the digital twin of a GPR antenna, was developed for artificial data generation. The process involves pre- and post-processing techniques to transform the three-dimensional data from the multichannel GPR system into two-dimensional datasets. This ensures minimal information loss and suitability for established two-dimensional object detection algorithms like the well-known YOLO (You Only Look Once) framework. Validation involved real-world measurements on a track with predefined buried objects. The entire pipeline, encompassing data generation, processing, training, and application, was automated for efficient algorithm testing and implementation. Artificial data show promise for better performance with increased training. Future AI and sensor advancements will enhance subsurface exploration, contributing to safer and more reliable railroad operations. [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) is a rapid and non-destructive geophysical technique widely employed to detect and quantify subsurface structures and characteristics. Its capability for time lapse (TL) detection provides essential insights into subsurface hydrological dynamics, including lateral flow and soil water distribution. However, during TL-GPR surveys, field conditions often create discrepancies in surface geometry, which introduces mismatches across sequential TL-GPR images. These discrepancies may generate spurious signal variations that impede the accurate interpretation of TL-GPR data when assessing subsurface hydrological processes. In responding to this issue, this study introduces a TL-GPR image alignment method by employing the dynamic time warping (DTW) algorithm. The purpose of the proposed method, namely TLIAM–DTW, is to correct for geometric mismatch in TL-GPR images collected from the identical survey line in the field. We validated the efficacy of the TLIAM–DTW method using both synthetic data from gprMax V3.0 simulations and actual field data collected from a hilly, forested area post-infiltration experiment. Analyses of the aligned TL-GPR images revealed that the TLIAM–DTW method effectively eliminates the influence of geometric mismatch while preserving the integrity of signal variations due to actual subsurface hydrological processes. Quantitative assessments of the proposed methods, measured by mean absolute error (MAE) and root mean square error (RMSE), showed significant improvements. After performing the TLIAM–DTW method, the MAE and RMSE between processed TL-GPR images and background images were reduced by 96% and 78%, respectively, in simple simulation scenarios; in more complex simulations, MAE declined by 27–31% and RMSE by 17–43%. Field data yielded reductions in MAE and RMSE of >82% and 69%, respectively. With these substantial improvements, the processed TL-GPR images successfully depict the spatial and temporal transitions associated with subsurface lateral flows, thereby enhancing the accuracy of monitoring subsurface hydrological processes under field conditions. [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) is a non-invasive technology that uses electromagnetic pulses for subsurface exploration. In the railroad sector, it is crucial to assessing soil layers and infrastructure, offering insights into soil stratification and geological features and aiding in identifying subsurface hazards. However, the automation of radargram analysis is impeded by the lack of ground truth—accurate real-world data used to validate machine learning models—thus affecting the deployment of advanced algorithms. This study focuses on generating high-quality simulated data to address the shortage of real-world data in the context of object detection along railroad tracks and presents a fully automated pipeline that includes data generation, algorithm training, and validation using real-world data. By doing so, it paves the way for significantly easing the future task of object detection algorithms in the railway sector. A simulation environment, including the digital twin of a GPR antenna, was developed for artificial data generation. The process involves pre- and post-processing techniques to transform the three-dimensional data from the multichannel GPR system into two-dimensional datasets. This ensures minimal information loss and suitability for established two-dimensional object detection algorithms like the well-known YOLO (You Only Look Once) framework. Validation involved real-world measurements on a track with predefined buried objects. The entire pipeline, encompassing data generation, processing, training, and application, was automated for efficient algorithm testing and implementation. Artificial data show promise for better performance with increased training. Future AI and sensor advancements will enhance subsurface exploration, contributing to safer and more reliable railroad operations.

Attenuation of radar waves in the subsurface can be quantified with a constant‐Q approximation through time‐frequency analysis. We implement the centroid frequency‐shift method and study Radar Imager for Mars' Subsurface Exploration (RIMFAX) data acquired along the Mars 2020 Perseverance rover traverse. Attenuation is among key media properties, but quantified estimates need to account for instrument characteristics and limitations in the analysis technique. We ensure accurate constant‐Q characterization and present the first estimates of radar attenuation in the upper 5 m of the shallow Martian subsurface. Over Jezero Crater Floor, constant‐Q is on average 70.4 ± 7.7, which equals an attenuation of −2.6 ± 0.3 dB/m at RIMFAX' 675 MHz center frequency. Regions comprising the Máaz or Séítah formations have similar attenuation properties that are consistent with magmatic lithologies. Plain Language Summary: First estimates of radar attenuation in the shallow Martian subsurface are presented. Estimates are from Jezero Crater Floor, along the drive path of the Mars 2020 Perseverance rover. Attenuation is among key media properties that describe radar wave propagation and can relate to lithological properties. Estimates of signal losses are consistent with magmatic lithologies and differences between distinct regions on Jezero Crater Floor are not detected. Key Points: First estimates of radar attenuation in the shallow Martian subsurface are on average −2.6 dB/m at the Radar Imager for Mars' Subsurface Exploration (RIMFAX) 675 MHz center frequencyResults are consistent with magmatic lithologies on the Jezero Crater FloorThe centroid frequency‐shift method is adequately implemented for RIMFAX analysis [ABSTRACT FROM AUTHOR]

Unfrozen free and non-free water between ice crystals in flat and hummock ice in the Yellow River exists as water films with varying contents based on ice temperature. These contents can affect the radar wave velocity of the ice despite its theoretical dependence on the crystal structure and ice body components. The unfrozen water content in ice depends on the ice temperature, which is controlled by the air temperature, solar radiation, and ice thickness. Winter air temperature and radar-detected ice thickness data observed at the Shisifenzi bend in the Yellow River from 2020 to 2021 were analyzed. The unfrozen water content in the ice was the primary factor influencing the accuracy of flat ice thickness detection. The heat flux at the ice–water interface in the Yellow River was determined. The evolution of ice thickness and temperature were simulated using a one-dimensional (1D) ice thermodynamic model forced by the local weather station data (i.e., air temperature, solar radiation, wind speed, and cloud cover). On this basis, the measured ice thickness data of 13 drill holes were combined to calculate 1251 thermodynamically simulated ice thicknesses consistent with the ice thickness detection time of the radar; therefore, statistical relationships regarding the influence of air temperature and the combined action of air temperature and ice thickness on the radar wave velocity in granular and columnar ice during air temperature increases and decreases were determined. Finally, the statistical relationship between the combined influence of air temperature and ice thickness on radar wave velocity was selected as a parameterization scheme to dynamically correct the radar wave velocity of flat ice. To enhance the radar detection accuracy for flat ice thickness, the radar wave velocity of ice was parameterized as a function. Given the presence of unfrozen frazil ice and accumulated broken ice blocks in the Yellow River, radar is suggested to detect the thickness of different types of ice in future research. [ABSTRACT FROM AUTHOR]

Chang'E-3, Chang'E-4 and Chang'E-5 were the first planetary missions with in-situ ground-penetrating radar (GPR) in their scientific payloads. Apart from the Chang'E missions, in-situ GPR has also been used in the Martian missions Tianwen-1 and Perseverance, establishing GPR as a mainstream and pivotal tool in the new era of planetary exploration. Despite its widespread use in planetary science, interpreting GPR data from the Chang'E-4 mission is still challenging, with varying and ambiguous interpretations offered by different researchers. This is primarily due to the complexity and heterogeneity of the Lunar subsurface, which results to a difficult to interpret radagram with low signal-to-clutter ratio. Clutter masks potential targets and makes interpretation a laborious and highly subjective process. To tackle this, we interpret the GPR data from Chang'E-4 mission using a novel processing paradigm based on un-supervised machine learning. A set of statistical attributes is initially calculated locally for different sliding windows in the investigated radagram. Subsequently, these statistical features are clustered into groups using un-supervised machine learning. The segmented radagram highlights boundaries between different formations, and reveals hidden structures previously unseen using typical processing approaches. The proposed framework is fully automatic and objective, facilitating processing, and increasing the overall reliability of the final interpretation. • Introducing a novel radar segmentation scheme based on unsupervised machine learning. • Use the segmentation scheme to cluster the radar data from the Chang'E-4 mission. • Identify previously unseen formations in the Von Kármán using solely data-driven interpretation tools. [ABSTRACT FROM AUTHOR]

The goal of this study is to develop a tool that will evaluate the moisture content gradient in the depth of reinforced concretes in the context of building safety. The monitoring of ageing phenomena, such as the corrosion of steel reinforcements, depends on the amount of water and on its gradient as they are directly related to the dielectric values of the concrete. In this paper, to obtain these values, we propose to solve an inverse problem for reinforced concrete. First, an experimental device based on radar measurements is proposed with its 3D numerical model. Next, we describe an inverse process to determine a dielectric profile according to the depth and validate it on measured data obtained for control samples. [ABSTRACT FROM AUTHOR]

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Yutu-2 – the rover from the Chang'E-4 mission – is the longest operational Lunar rover, and the first rover to land on the far side of the Moon. It is the second planetary rover to be equipped with ground-penetrating radar (GPR), one of the few in-situ geophysical techniques used in planetary exploration. Since landing in 2019, Yutu-2 has travelled more than 1 kilometre in the Von Kármán (VK) crater, and has been able to investigate the dielectric properties of the shallow Lunar ejecta using its on-board high frequency GPR channels. In this paper, we use advanced signal processing and frequency attributes to infer a detailed dielectric structure of the first ≈ 30 metres of the subsurface, providing valuable information on the ilmenite content of the landing site. Both the dielectric properties and the ilmenite content suggest a shallow sequence of Imbrian basaltic layers overlaying a low-ilmenite ejecta blanket. • Detailed imaging of layered structures at the landing site of Chang'E-4 mission. • Inferring the presence of a shallow sequence of basaltic lava layers. • Using frequency attributes to estimate the ilmenite content of subsurface layers. [ABSTRACT FROM AUTHOR]

We apply the magnetic resonance sounding (MRS) method to investigate a firn aquifer in the south‐east region of the Greenland ice sheet. Our study aims to delineate and estimate the volume of the recently discovered water stored within the firn (compacted snow) that remains liquid throughout the year. We develop and test successfully a methodology for joint use of MRS and ground‐penetrating radar (GPR). This non‐invasive geophysical approach is particularly well‐adapted to glacier conditions and has a promising future for in situ investigation of water distribution in glaciers. At our field site, MRS showed an aquifer located at variable depths between 20 and 30 m beneath the ice‐sheet surface. At the monitoring site, both MRS and GPR show an increase in the water volume stored between April 2015 and July 2016. MRS estimates suggest that the volume increased by approximately 28%. [ABSTRACT FROM AUTHOR]

Disaster due to inundation is one of the major threats of coal mines. Sudden heavy inrush of high volume of water from the unapproachable and unknown waterlogged workings in underground mines is defined as inundation. There have been several instances of inrush of water due to old galleries getting connected by new development headings, resulting in disasters involving heavy fatalities and loss of machines. This type of disaster has occurred in many coal producing countries and may occur in future until a suitable tool to investigate barriers thickness is in regular use. Directorate General of Mines Safety (DGMS) has stipulated that a safety barrier thickness of not less than 60 m must be maintained between abandoned workings and contemporary mine developments. It has been estimated that a large number of underground coal mines in India are under threat of adjacent unknown waterlogged mine workings. Therefore, evaluation of barrier thickness up to 60 m is essential to prevent mine disasters due to inundations. Considering the above facts, a new GPR system named MineVue radar is developed having depth of penetration of 60 m subject to geo-mining conditions of Indian coal mines first time in the world. Final trial of the developed MineVue radar system was done at the Kachhi Balihari colliery of Bharat Cocking Coal Limited (BCCL), Dhanbad. The validation of GPR data in the known mine sites were done with accurate existing mine-plans to establish the reliability and confidence of mine operators, policy makers and safety personnel. [ABSTRACT FROM AUTHOR]

The radar technique prospects the subsoil with electromagnetic waves with frequencies between 10 and 1200 Mhz. A reflection radar image shows contrasts of the subsoil generated by its inhomogeneous electromagnetic properties. The velocity of the dielectric constant, correlated with mineral fabric, structure and water contained in rocks. Meanwhile lab assays, correlations between this properties for sand, cloy and a mixture of the, were stablished.La técnica del geo-radar, o G.P.R. por su sigla en inglés (Ground Penetrating Radar), es una forma de prospección del subsuelo utilizando ondas electromagnéticas con frecuencias entre 10 y 1200 Mhz. Una imagen de geo-radar obtenida por reflexión contiene contrastes generados por la variación espacial de las propiedades electromagnéticas. La velocidad de las ondas electromagnéticas en un suelo depende fundamentalmente de la constante dieléctrica equivalente, la cual se puede correlacionar con la fábrica, la estructura y el contenido de agua. Por medio de pruebas en laboratorio se establecieron correlaciones para arena, recebo y arcilla.

We propose a new approach to model ground penetrating radar signals that propagate through a homogeneous and isotropic medium, and are scattered at thin planar fractures of arbitrary dip, azimuth, thickness and material filling. We use analytical expressions for the Maxwell equations in a homogeneous space to describe the propagation of the signal in the rock matrix, and account for frequency-dependent dispersion and attenuation through the empirical Jonscher formulation. We discretize fractures into elements that are linearly polarized by the incoming electric field that arrives from the source to each element, locally, as a plane wave. To model the effective source wavelet we use a generalized Gamma distribution to define the antenna dipole moment. We combine microscopic and macroscopic Maxwell's equations to derive an analytic expression for the response of each element, which describes the full electric dipole radiation patterns along with effective reflection coefficients of thin layers. Our results compare favorably with finite-difference time-domain modeling in the case of constant electrical parameters of the rock-matrix and fracture filling. Compared with traditional finite-difference time-domain modeling, the proposed approach is faster and more flexible in terms of fracture orientations. A comparison with published laboratory results suggests that the modeling approach can reproduce the main characteristics of the reflected wavelet. [ABSTRACT FROM AUTHOR]

In this work we present an analysis of the applicability of ground penetrating radar (GPR) to karstic hazard evaluation in urban areas by means of several case studies. The main objective is to characterize the origin of pathologies in buildings and other facilities, and of subsidence processes, and to identify their causative phenomena in the subsoil. This study involves the analysis of resolution, penetration characteristics and noise affecting GPR signals in urban areas. The analyzed case studies are located in the Central Ebro Basin (NE Spain), where the main hazards are related to mantled karst (solution of evaporites below alluvial deposits). The studied examples show that in areas affected by karst activity with medium to high subsidence rates, interpretation of GPR profiles allows defining collapses, subsidence, surficial repairs (either historical or recent) and underground cavities. [ABSTRACT FROM AUTHOR]