GPR Signal Research Articles

Assessment of Soil Horizons and Their Matric Potential from Ground-Penetrating Radar Signal Attributes

Soil plays significant roles in different phases and in the continuous existence of human life. Its comprehensive knowledge, particularly as related to its physical characteristics, enhances its utilization, conservation, and management. The traditional methods of soil study are characterized with some pitfalls such as much time needed to perform such assessments. There are also issues of invasiveness that affect the soil structures and discrete sampling that may not reflect true spatial attributes in the outcome of such techniques. These problems are largely due to the concealing nature of soil layers that made its thorough evaluation difficult. In this study, an alternative geophysical approach has been adopted. The technique is the ground-penetrating method (GPR) that utilizes electromagnetic pulse energy via its equipment’s sensors, which can allow the investigation of soil properties, even in its concealing state. This study aimed at qualitatively evaluating the soil horizons and the matric potentials using the GPR signal attributes within the unsaturated zone with a view of having insight into the test field’s characterization. Field data measurements were obtained using MALA ProEX GPR equipment with its accessories manufactured by MALA Geosciences, Stockholm, Sweden. Evaluation of the processed field data results and computed attributes show soil characteristics variations with depth that was interpreted as the layers. This can be seen from the GPR data presentation as an image representing the subsurface of the zones of propagation of the pulse energy. Spectral analysis of the GPR signals allows for the delineation of two zones of contrasting features, which were tagged as high and low matric potentials. Although the conventional direct measurement of the matric potential was not made at the time of the study to complement and confirm the veracity of the approach, the results indicate the possibility of the approach towards a quick and in situ technique of soil investigations. Such evaluation may be valuable input in precision agriculture where accurate data are sought for implementation.

A novel moisture damage detection method for asphalt pavement from GPR signal with CWT and CNN

To locate the moisture damage area in asphalt pavement, an automatic detection method by leveraging the state-of-the-art deep learning approach and continuous wavelet transform (CWT) method from high frequency GPR signal was presented. A numeric simulation and a laboratory experiment were employed to analyze the response of GPR signal in moisture damage area. GPR signals were transferred to time-frequency domain by using a CWT method, before comparing CWT results among normal pavement, moisture and bridge joints. Moisture damage datasets, including 8215 traces of moisture damages, 8215 traces of normal pavement and 7643 traces of bridge joints, were extracted from GPR field survey of bridge pavement with 2.3 GHz antenna. The maximum and mean values of CWT results were obtained from the dataset and used to normalize the CWT dataset. Typical classification models, including Resnet50, ResNet18, ShuffleNet, EfficientNet, NasNetmobile and DenseNet, were trained and compared on the CWT dataset. The result indicates that the CWT features among normal pavement, moisture damage and bridge joints have significant differences. Moreover, the energy distribution in the CWT image can represent the moisture damage depth and width information, proving that the CWT method is effective for extracting moisture damage features from GPR signal. The overall performance of ResNet50 model is best with high accuracy and high efficiency in moisture detection compared to other models. Experimental results proved the promising performance of our approach in detecting moisture damage in asphalt pavement, and this method could also be used for subsurface target detection in other GPR application.

Interpretation of georadar data to search for hidden isolated objects

This article considered the possibilities of using a radar device in archeology. A geophysical method has been chosen that makes it possible to find underground archaeological sites without excavations. GPR signals are recorded as a radargram. Interpretation of radargrams makes it possible to make a predictive image of underground objects. However, the interpretation of radargrams is of a commercial nature. Therefore, the task of developing its own methods for interpreting radargrams is relevant. With the help of a geophysical GPR instrument, mounds, located far from settlements in the Kyzylorda region, were investigated. Three objects were chosen for the study: two barrows and a strip of land between the barrows. The latter has been investigated to determine if there is a connection between the two burial mounds. A marking scheme for the study area has been created. The problem under study requires the use of a non-destructive method. In order to significantly save time and money compared to existing methods of visual inspection of these objects with subsequent archaeological excavations, experimental studies were carried out with a step of 0.2 m using a geophysical instrument with 0.15 m antennas. Continuous areal surveys of three squares were made. Tests, monitoring, and scientific measurements were carried out. GPR data for predicting hidden isolated objects were processed using special built-in software. Recommendations to archaeologists are given.

Study on Estimation of Cavity Size in Back Side of Plain Tunnel Concrete Lining using Low-frequency GPR Signal Changes

Study on Estimation of Cavity Size in Back Side of Plain Tunnel Concrete Lining using Low-frequency GPR Signal Changes

Ground penetrating radar in temperate ice: englacial water inclusions as limiting factor for data interpretation

Abstract Ground penetrating radar (GPR) has been extensively used in glaciology to infer glacier's ice thickness, liquid water content, water drainage pathways, and other properties. The interpretation of such GPR data is not always straightforward and for temperate glaciers, the signal is often affected by strong scattering and attenuation. It has often been suggested that such effects originate from englacial water inclusions, since water and ice have a large contrast in their di-electric permittivity. To investigate such effects quantitatively, we perform an extensive numerical modeling study of GPR signals. By exploring how different liquid water contents (LWC) and water-inclusions size affect the GPR signal, we show that their effects are much larger than the potential presence of a wet snowpack or a heterogeneous distribution of ice permittivity. In particularly, we show that the presence of such water inclusions is a necessary and sufficient condition for reproducing the typical characteristics of GPR data acquired in the field. Further, we find that for 25 MHz GPR antennas, a bulk LWC $\gtrsim$ 0.2%, associated with decimeters-scale water inclusions already limits bedrock detectability for ice thicknesses $\gtrsim 100$ m. Since these values are typical for Alpine glaciers, they clarify why the quality of GPR data is often poor in such environments.

Biorthogonal wavelet energy entropy method with different time windows for strong interference processing of GPR signals

In the light of the shielding effect of the strong reflection signal generated by the steel bars and the inhomogeneous of concrete materials on the weak signal in the tunnel lining detection, a high-resolution GPR image processing method of biorthogonal wavelet energy entropy in different time windows is proposed. Wavelet analysis has the characteristics of multiresolution, and wavelet entropy can represent the energy distribution characteristics of signals in different time windows with different scales. Firstly, the discrete biorthogonal wavelet transform is applied to decompose the original GPR image into subimages with different frequencies and different spatial local changes. Secondly, appropriate time windows are selected for wavelet entropy adaptive threshold processing of each subimage in the light of the different amplitude ratio of effective signal to strong interference in each subimage, and finally the reconstructed image after removing the strong reflection is spectrally whitened. Both the forward simulations and actual measurement results show that the method can effectively remove strong reflection interference, clear weak signals, and maintain the continuity of the reflection events, and compared to the conventional pulse deconvolution, predictive deconvolution and wavelet entropy methods with the same time window, this method has a more thorough interference removal effect, and the effective signal performance is more obvious, which proves the effectiveness and accuracy of the proposed method in improving the resolution of GPR image and highlighting weak signal.

Velocity analysis of a lateral wave

In practice, the reflected EM signal cannot be clearly observed in GPR data due to the high water content and other reasons. However, the antenna coupling signal through the ground interface is dominated in all the GPR measurements. This direct coupling signal that travels through the ground interface is called a lateral wave. The properties of the lateral wave directly depend on the subsurface properties, especially electrical parameters. We have numerically analyzed a lateral wave and its velocity. Subsequently, the relationship between lateral wave and dielectric permittivity was determined by polynomial regression. Analytically, it is challenging to analyze a lateral wave due to the parameters that can influence wave propagation. Antenna characteristics, surface roughness, etc need to be considered. Numerically, we designed a GPR system with a subsurface layer and observed a lateral wave. This numerical analysis can give a chance to use a lateral wave for near-surface soil water content. This analysis gives a more precise estimation of surface water content. Moreover, we analyze the antenna height effect that influences radar signals. We numerically observed that the GPR signal is highly affected by antenna height. The antenna height effect depended on the wavelength of the applied electromagnetic wave. By adjusting the antenna height, the unobservable GPR signal can be clearly detected.

Computer Modeling of the Outgoing GPR Signal

This paper considers a mathematical model to reconstruct the shape and tabular value of the source based on real signal data from a Loza-V series GPR receiver. A geoelectric equation in a cylindrical coordinate system is chosen as the mathematical model. Experiments, using GPR, were conducted on a homogeneous area of clean river sand, with known geoelectric properties. In this case, the equation in question is reduced to the Riccati differential equation using a special function substitution. This allowed us to obtain an explicit expression linking the spectrum function describing the response of the medium (the real radar data) and the spectrum function describing the source behavior. From the found source spectra, using inverse Fourier transforms, the emitted source itself is reconstructed in tabular form. The methodology of source reconstruction was carried out at different locations of the receiver antenna from the source antenna. In practice, geophysicists are interested in the physical characteristics of heterogeneity depending on spatial coordinates. For numerical solution of inverse coefficient problem it is necessary to have tabular value of disturbance source and tabular values of reflected signals (GPR data) at measurement points. To solve these problems we have developed an algorithm of source reconstruction and, as a consequence, determination of media response corresponding to real GPR data at the points of observation. A series of numerical calculations demonstrating the effectiveness of the considered computer model for source recovery have been carried out.

Three-dimensional characterization of karstic dissolution zones, fracture networks, and lithostratigraphic interfaces using GPR cubes, core logs, and petrophysics: Implications for thief zones development in carbonate reservoirs

Fractures and karstic dissolution features have been recognized to significantly affect subsurface fluid flow on a range of scales in carbonate rocks. However, due to the information gap between seismic and borehole scales, characterizing these features is a real challenge. We present a three-dimensional multidisciplinary approach to identify the main factors controlling the formation of connected rock volumes composed by permeable karstic dissolution zones. We investigate two outcrops in the Jandaíra Formation, which is an intensely fractured and karstified carbonate platform in the Potiguar Basin, Brazil. Two GPR cubes are jointly interpreted with cored boreholes, borehole images, petrophysical profiles, and thin sections. We verified that attenuated zones of GPR signal are related to secondary carbonate changes caused by fracturing and/or diagenetic alterations, leading to the development of relatively high secondary permeability. At least three types of attenuation/karstic zones might occur: fractured or broken zones affected by fracture enlargement due to dissolution, zones submitted to intense diagenetic alterations, and void spaces as a final end-member of these two processes. Fractures are preferential routes to fluid flow, thus contributing to increase dissolution processes, particularly in layers having relatively high values of primary matrix porosity and permeability. On the other hand, relevant diagenetic alterations might occur in layers that contain high concentration of stylolites. As a result of interconnecting dissolved stylolites, zones of relatively high secondary permeability can be created regardless of the primary values of matrix porosity and permeability. Geobodies of connected volumes of karstic zones often present tabular shapes and are delimited by subvertical fractures and subhorizontal lithostratigraphic interfaces. In the reservoir scale, these tabular geobodies might compose highly connected permeable volumes of altered carbonate rocks that constitute thief zones or super-K layers.

Formation Processes of Gully-side Debris-Cones Determined from Ground-Penetrating Radar (Mt. Unzen, Japan)

Volcanic gullies develop U-shape cross-profiles due to the lahars that shape them after eruptive events. Over time, the processes of sediment-transfer change and the erosion of sub-vertical walls become a leading process. It results in debris-cones at their foot. However, the processes that generate these landforms is still unclear. Indeed, the surface is the one of a cone or a “steep debris-fan”, but are these diffusive landforms starting through progressive regressive-erosion of the wall, or do they follow an original collapse? This we do not know, and as the material is poorly-sorted with a mixture of unconsolidated fine sands to large clasts, digging a trench is not possible as it destroys the material structure. Therefore, the present contribution aims to define the development mechanisms of the side-wall debris-cones using Ground Penetrating Radar imaging, working in the Tansandani Gully at Unzen Volcano (Japan). The GPR used in the study is a Mala Ramac Pro-Ex mounted with a 500 MHz shielded antenna. The GPR signal penetrated up to 4–5 m depth and the velocity was homogeneous on average through the different material layers and at the different location, although at depth variations occurred. The structure of the units in the radargrams present units' parallel to the surface for the first 40 to 60 cm, with underneath the presence of more irregular prograding units, with eventually underneath a set of units that are structureless and often rich in blocks. The two lower structureless-units are not always present and one of the debris-cone only showed a set of rough subparallel units. This differences are the result of the debris-cones being generated by (1) at first a wall collapse or by rapid water-borne processes creating (2) bulk prograding units, which have to be put in place during a heavy-rainfall event. Finally, near the surface, the (3) thin subparallel units are most probably post-rainfall deposition, resulting from gravity process in dry-material. This can be inferred because there is no evidence of erosion or remobilization in layers and the process has been observed in the field. For the observed debris-cones, their formation is dominated by a wall collapse, which is then recovered by finer-grained units deposited sub-horizontally to the surface.

Statistical Features of Georadar Signals Obtained by Probing Horizontal Layered Media in Permafrost

Relevance. To study the structure and properties of rock masses in the permafrost zone, such a method of geophysics as ground penetrating radar is successfully used. The existing methods of GPR measurements make it possible to obtain large volumes of reliable data on the layered structure of permafrost rocks. The methodological support for processing and interpreting data is developed much worse. Thus, manual and semi-automatic methods are used to identify the in-phase axes of georadar signals confined to the boundaries of rock layers, which significantly slows down the process of cameral work. Existing methods for automating the selection of in-phase axes of georadar signals do not always successfully cope with this task, since the statistical characteristics of georadar traces obtained by probing a horizontally layered media are very variable. The purpose of the research is to establish the statistical features of georadar signals that form the in-phase axes obtained by probing horizontally layered media in permafrost. Research methods – statistical analysis of the results of field georadar measurements in the Anabar region of the Republic of Sakha (Yakutia) at the site of the Mayat diamond deposit (AO Almazy Anabara) using the GPR OKO ABDL-Triton. Conclusions. The research of the amplitude characteristics of GPR signals that form the in-phase axes showed the presence of a random component, which significantly affects the recorded GPR wave field. Using the results of field measurements of horizontally layered media as an example, a change with increasing depth of the main statistical characteristics, as well as the distribution of amplitude values (normal–uniform–normal) was established. The results obtained will be very useful both in interpreting georadar measurement data and in improving the accuracy of modeling the propagation of ultra-wideband electromagnetic waves in horizontally layered media, and can also be used to refine the previously developed model of a georadar section of a frozen rock mass.

Ground Penetrating Radar detection of unmarked historic graves at the Fairlawn Cemetery in Stillwater, Oklahoma

AbstractGround Penetrating Radar (GPR) survey was conducted to detect historic unmarked graves from the period of the Civil War (1861–1865) at the Fairlawn Cemetery in Stillwater, Oklahoma. The GPR survey at the Fairlawn Cemetery will help preserve the unmarked historic graves if they exist or clear sections of the cemetery for possible expansion. GPR detection of historic graves are often a challenge as these graves are made of wooden boxes, bones and coffins, with no metal caskets or concrete burial vaults. It was even more challenging to detect unmarked graves in this study as the cemetery is covered with iron‐rich silty clay soil, which attenuates the GPR signals. We conducted the GPR survey along a grid consisting of 44 parallel 30‐m‐long profiles spaced at 50‐cm intervals using the 400‐MHz antenna. The acquired GPR data were processed as 2D profiles and produced a pseudo‐3D GPR volume to resolve the unmarked graves. Multiple features extracted from the pseudo‐3D volume at depths ranging from 0.7 to 1.3 m aligned along three north–south rows. Based on the dimensions, orientation, distribution and depth of burial of the anomalous features relative to the recent graves, we interpreted these features as unmarked graves. This study has demonstrated the GPR as an effective non‐invasive technique in detecting historical unmarked graves that contain no metal caskets or concrete burial vaults. This work will contribute not only to the science of historical archaeology but also to prehistorical archaeology, as caskets were not typically part of the prehistorical burials, and the modern‐day archaeology, particularly in the cases of mass graves in recent conflicts.

GPR Energy Attribute Slices Based on Multivariate Variational Mode Decomposition and Teager–Kaiser Energy Operator

The GPR signals appear nonlinear and nonstationary during propagation. To evaluate the nonstationarity, the empirical mode decomposition (EMD) and its modifications have been proposed to localize the variations of energy and frequency components over time. Among the EMD−based algorithms, the variational mode decomposition (VMD) is one of the representative methods. It eliminates the drawbacks of EMD, to some extent, but is still executed in one dimension. In this work, the multivariate variational mode decomposition (MVMD) algorithm is introduced for decomposing the GPR B-scans into several IMF-slices in two dimensions, which inherits the advantages of the VMD and considers the stratigraphic constraints. Then, by applying the Teager–Kaiser energy operator (TKEO) within each IMF-slice, a novel energy attribute is formed and termed as the “TKEO-slices”. The proposed TKEO-slices can localize the energy attribute of geophysical information of different scales with good stratigraphic continuity. The proposed scheme is evaluated by the synthetic benchmark, model data, and field data. Compared with the VMD−based scheme and the classic instantaneous amplitude, the proposed TKEO-slices show better resolution and lateral continuity.

Background clutter amplitude and frequency of GPR signals to analyse water content in sedimentary deposits: Urban infrastructure environment

Soil site studies are crucial in the analysis of seismic hazard in populated areas. This study focusses on the use of the Ground Penetrating Radar as a non-destructive geophysical method to analysis the water content of a sedimentary basin of a local urban area in Cervantes Parks in Barcelona city. Main objective of this work is to understand further the local seismic soil site, and analysis the background clutter amplitude and frequency of the GPR signal applied on the seasonal changes of the underground water content. Changes produces in the GPR signal could be associated to the changes of the ground material due to the existence of water content and water flow, which influence the grain size distribution of the soil characterisation.Previously, several methodologies have been applied to determine the changes of the ground material due to the existence of water content and most importantly effect of the seasonal changes on the soil characterisation. GPR has been applied as a new technology and non-invasive to further analysis water content in shallow geology. Methodology applied on this study compromised in four different phases; Two seasonal data collection using 100 MHz centre frequency shielded antenna in both dry and wet season, radar images are proceeded with common post-processing approaches, following more innovative processing approach based on the Fast Fourier Transform (FFT) method in order to analysis background clutter amplitude and frequency spectrum to achieve an accurate interpretation of underground water content activities, in conclusion a comparative study of the results driven from radar images are elaborated considering historical knowledge. Results show that GPR is an efficient technique to analysis water content invasively considering low frequency antennas to achieve deeper penetration depth in sedimentary deposits, and predict shifting and increasing of the underground streams due to changes in weather conditions. Results could contribute to the enhancing local seismic site behaviour in populated areas considering continuous monitoring of underground water activities in sedimentary basin sites.

Examinating GPR based detection of defects in RC builds

The Ground Penetrating Radar is a device which can be used for non-destructive inspection of civil engineering structures such as reinforced concrete buildings and bridges. Because of its ability to detect defects and provide reliable image of the substructure, it has attracted large interest from both practitioners and researchers in the field of health monitoring of vital structures. The objective of this work is to analyze detectability of defects in reinforced concrete structures by considering the presence of a defect which can attenuate GPR signals. Defects embedded in the structure can in fact cause significant changes in the intensity of the hyperbolic like reflection patterns generated by reinforcement bars. To assess this effect, a numerical simulation study of GPR data was conducted by using the GprMax software which is based on finite differences time domain method. The proposed approach has enabled to study the modification affecting the radargram due to the presence of a defect of finite size.

Optimised Extraction of Archaeological Features from Full 3-D GPR Data

The use of non-invasive methodologies is becoming essential for archaeological research, and ground penetrating radar is one of the most important techniques to obtain high resolution information. In this paper we present the analysis of a full 3-D GPR dataset integrated with a high-resolution photogrammetric survey acquired in a Roman archaeological site located in Aquileia (Northeast Italy) within the partially excavated area known as “Fondo Pasqualis”. We evaluated the importance of dense and accurate data collection and of processing of the GPR signal for characterization of the archaeological features. We further discuss the parametrization and the applicability of GPR attributes, in particular amplitude-based and coherence attributes, to better identify and characterise the archaeological buried targets. Furthermore, autopicking procedures for isosurfaces mapping were critically evaluated with the objective of detecting complex structures. The final interpretation of all the GPR features, with the support of digital terrain modelling and orthophotos from unmanned aerial vehicles, guided the archaeologists to open and excavate newly selected areas, which revealed interesting structures and contributed to the understanding of the historical events that characterized the Aquileia city.

Comparative Analysis of Spectral Characteristics of Pulse GPR Signals for Road Pavement Assessment

Comparative Analysis of Spectral Characteristics of Pulse GPR Signals for Road Pavement Assessment

Development and Validation of Nomograms Based on Gamma-Glutamyl Transpeptidase to Platelet Ratio for Hepatocellular Carcinoma Patients Reveal Novel Prognostic Value and the Ratio Is Negatively Correlated With P38MAPK Expression.

BackgroundEarly prediction of recurrence and death risks is significant to the treatment of hepatocellular carcinoma (HCC) patients. We aimed to develop and validate prognosis nomogram models based on the gamma-glutamyl transpeptidase (GGT)-to-platelet (PLT) ratio (GPR) for HCC and to explore the relationship between the GPR and inflammation-related signaling pathways.MethodsAll data were obtained from 2000 to 2012 in the Affiliated Hospital of Qingdao University. In the training cohort, factors included in the nomograms were determined by univariate and multivariate analyses. In the training and validation cohorts, the concordance index (C-index) and calibration curves were used to assess predictive accuracy, and receiver operating characteristic curves were used to assess discriminative ability. Clinical utility was evaluated using decision curve analysis. Moreover, improvement of the predictive accuracy of the nomograms was evaluated by calculating the decision curve analysis, the integrated discrimination improvement, and the net reclassification improvement. Finally, the relationship between the GPR and inflammation-related signaling pathways was evaluated using the independent-samples t-test.ResultsA larger tumor size and higher GPR were common independent risk factors for both disease-free survival (DFS) and overall survival (OS) in HCC (P < 0.05). Good agreement between our nomogram models’ predictions and actual observations was detected by the C-index and calibration curves. Our nomogram models showed significantly better performance in predicting the HCC prognosis compared to other models (P < 0.05). Online webserver and scoring system tables were built based on the proposed nomogram for convenient clinical use. Notably, including the GPR greatly improved the predictive ability of our nomogram models (P < 0.05). In the validation cohort, p38 mitogen-activated protein kinase (P38MAPK) expression was significantly negatively correlated with the GPR (P < 0.01) and GGT (P = 0.039), but was not correlated with PLT levels (P = 0.063). And we found that P38MAPK can regulate the expression of GGT by quantitative real-time PCR and Western blotting experiments.ConclusionsThe dynamic nomogram based on the GPR provides accurate and effective prognostic predictions for HCC, and P38MAPK-GGT may be a suitable therapeutic target to improve the prognosis of HCC patients.

Forward modelling on GPR responses of subsurface air voids

Along with the development of urbanization, an increasing number of subsurface voids in urban cities can have serious effects on the expected functionality of key infrastructure elements such are roads. Ground penetrating radar is an effective technique for imaging the subsurface and detecting such air voids. The GPR responses of air voids with different horizontal width were quantitively investigated in this study using forward modelling: empirical experiments in both laboratory and site; as well as numerical simulations with FDTD. Two typical road constructions were modelled: reinforced concrete pavements and bituminous pavements, where the majority of underground utility networks are buried underneath. Pulse GPR signals having two centre frequencies: 600 MHz and 200 MHz were simulated. It was observed that the ratio of void size and GPR signal wavelength would result in various patterns in the GPR B-scans: they can be a hyperbola, a cross pattern, a bowl shape pattern, and a plain reverberation pattern. And GPR responses of voids under road structures were distorted by reinforcement. With signatures of air voids appeared in GPR B-scans through validation by lab experiments and ground truthing, confidence of void identification will be enhanced.

Multi-frequency and multi-attribute GPR data fusion based on 2-D wavelet transform

High frequency GPR signals offer high resolution while low frequency GPR signals offer greater depth of penetration. Effective fusion of multiple frequencies can combine the advantages of both. In addition, GPR attribute analysis can improve subsurface imaging, but a single attribute can only partly highlight details of different physical and geometrical properties of subsurface potential targets. In order to overcome these challenges, we implement an advanced multi-frequency and multi-attribute GPR data fusion approach based on 2-D wavelet transform utilizing a dynamic fusion weight scheme derived from edge detection algorithm, which is tested on data from a small glacier in the north-eastern Alps by 250 & 500 MHz central frequency antennas. Besides, information entropy and spatial frequency are developed as quantitative evaluation parameters to analyze the fusion outcomes. The results demonstrate that the proposed approach can enhance the efficiency and scope of GPR data interpretation in an automatic and objective way.