Frequency Ground Penetrating Radar Research Articles

Ground-penetrating radar dual-parameter full waveform inversion based on finite domain method

Abstract Ground penetrating radar (GPR) is a crucial method for shallow geophysical exploration method. GPR full waveform inversion (FWI) utilizes all available information including dynamics and kinematics, and theoretically achieving the highest imaging accuracy. However, a significant challenge for FWI is its low computational efficiency, which fails to meet the real-time requirements in actual exploration. To address this issue, we propose a finite domain method (FDM) based on the attenuation characteristic of high frequency GPR electromagnetic waves. This approach limits the calculation to a finite domain, thereby mitigating the excessive computational burden. We determine the size of the finite domain from absorption attenuation, wavefront diffusion, and scattering loss. Numerical experiments demonstrate that compared with traditional FWI, FWI based on FDM reduces the calculation time by more than 5 times.

Detection of Vertebrate Skeletons by Ground Penetrating Radars: An Example from the Ica Desert Fossil-Lagerstätte

We present a technique for the detection of vertebrate skeletons buried at shallow depths through the use of a ground-penetrating radar (GPR). The technique is based on the acquisition of high-resolution data by medium-to-high frequency GPR antennas and the analysis of the radar profiles by a new forward modelling method that is applied on a set of representative traces. This approach allows us to obtain synthetic traces that can be used to build detailed reflectivity diagrams that plot spikes with a distinct amplitude and polarity for each reflector in the ground. The method was tested in a controlled experiment performed at the top of Cerro Los Quesos, one of the most fossiliferous localities in the Ica Desert of Peru. We acquired GPR data at the location of a partially buried fossil skeleton of a large whale and analyzed the reflections associated with the bones using the new technique, determining the possible signature of vertebrae, ribs, the cranium (including the rostrum), and mandibles. Our results show that the technique is effective in the mapping of buried structures, particularly in the detection of tiny features, even below the classical (Ricker and Rayleigh) estimates of the vertical resolution of the antenna in civil engineering and forensic applications.

Bayesian optimization based extreme gradient boosting and GPR time-frequency features for the recognition of moisture damage in asphalt pavement

Moisture damage is one of the major defects in asphalt pavement, and will evolve into potholes in a short time which will affect traffic safety. Ground Penetrating Radar (GPR) is an effective non-destructive testing (NDT) method for detecting moisture damage but its data explanation replies on human experience and subjects to labor intensive. To address this issue, an automatic detection method based on extreme gradient boosting (XGBoost) combined with Bayesian hyper-parameter optimization (BHPO) was proposed to detect moisture damage area from GPR traces. High frequency GPR antenna with 2.3 GHz was used to detect the moisture damage area from simulation, laboratory and field tests, and moisture damage dataset with 7960 traces was collected. Thirty time-frequency parameters were extracted from each GPR trace, normalized to unify the three data source, and then optimized into 12 sensitive parameters by feature importance method. These 12 parameters were used to build the recognition model with XGBoost, and the model tuning parameters were optimized by BHPO. To obtain optimization model, random forest (RF) and artificial neural network (ANN) were also trained with BHPO, and compared with XGBoost model. The results indicate that performance of XGBoost model with BHPO achieves the highest accuracy and lowest time cost both in moisture damage and normal trace classification, the accuracies for moisture damage are XGBoost (96.9%) > ANN (95.6%) > RF (95.4%), respectively, and normal are XGBoost (96.5%) > RF (96.1%) and ANN (96.0%), respectively. On this basis, field tests were conducted by core samples, which verified the correct result of XGBoost model. Our method provides a swift and accurate method to locate subsurface targets directly from GPR signals.

Evaluation of the variation of the GPR frequency spectra created by the activities of earthworms

The analysis and utilization of frequency spectrum in emission signals from ground penetrating radar (GPR) are essential for investigating soil characteristics and enhancing urban management. This research focuses on assessing the effectiveness of earthworm activities in improving rainwater management in regions with clay soil, where water infiltration is challenging. Specifically, we examined the impact of two earthworm species, Lumbricus terrestris and Aporrectodea caliginosa, as well as a combination of both, on the permeability of clay loam soil. To evaluate earthworm activities, a gravity-driven film flow setup with nine tanks was employed. Furthermore, we suggest utilizing the Discrete Fourier transform to analyse the frequency spectra of different data types (traces, transects, and the average of tanks) and comprehend their influence on earthworm behavior. To investigate the relationship between fluctuations in infiltration velocity and the frequency spectrum signal over time and activity position, a correlation analysis was performed using linear regression models. The goodness of fit was assessed based on the coefficient of determination (R2). For the earthworm species L1, L2, and L12, the R2 values were determined as 0.8858, 0.847, and 0.9493, respectively. These results demonstrate that the frequency domain was derived from variations in ground penetrating radar signals, and a significant correlation exists between infiltration velocity and spectra influenced by earthworm activity.

Multi-Frequency GPR Data Fusion through a Joint Sliding Window and Wavelet Transform-Weighting Method for Top-Coal Structure Detection

Top-coal structure detection is an important basis for realizing effective mining in fully mechanized cave faces. However, the top-coal structure is very complex and often contains multi-layer gangues, which seriously influence the level of effective mining. For these reasons, this paper proposes a novel multi-frequency ground-penetrating radar (GPR) data-fusing method through a joint sliding window and wavelet transform weighting method to accurately detect the top-coal structure. It possesses the advantages of both high resolution and great detection depth, and it can also integrate multi-frequency GPR data into one composite profile to interpret the internal structure information of top coal in detail. The detection procedure is implemented following several steps: First of all, the multi-frequency GPR data are preprocessed and aligned through a band-pass filter and a zero offset elimination method to establish their spatial correspondences. Secondly, the proposed method is used to determine the time-varying weight values of each frequency GPR signal according to the wavelet energy proportion within the sliding window; also, the edge detection algorithm is introduced to improve the fusion efficiency of the wavelet transform so as to realize the effective fusion of the multi-frequency GPR data. Thirdly, a reflection intensity model of multi-frequency GPR signals traveling in the top-coal is established by using the stratified identification method, and then, the detailed top-coal structure can be inversely interpreted. Finally, the quantitative evaluation criteria, information entropy (IE), space–frequency (SF) and Laplacian gradient (LG), are used to evaluate the multi-frequency GPR data fusion’s effectiveness in laboratory and field environments. The experimental results show that, compared with the genetic, time-varying and wavelet transform fusion method, the fusion performance of the presented method possesses higher values in the IE, SF and LG evaluation criteria, and it also has both the merits of high resolution and great detection depth.

Evidence of shallow basaltic lava layers in Von Kármán crater from Yutu-2 Lunar Penetrating Radar

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.

Study on the penetration capability of GPR for the steel-fibre reinforced concrete (SFRC) segment based on numerical simulations and model test

The SFRC segment is gaining attention in shield tunnels due to their better mechanical properties. However, the existence of steel fibres poses a greater difficulty when attempting to utilize ground penetrating radar (GPR) for nondestructive quality inspection compared to conventional reinforced concrete segments. This paper presented a refined numerical model of SFRC segments with gprMax software, to investigate the penetration characteristics of GPR. The numerical model incorporated four different steel fibre contents, namely 0%, 0.5%, 2.5%, and 5%. The model also included an internal void and a surface metal plate to compare and analyze the waveform characteristics of GPR with the normal sections of the segment. The orthogonal test of numerical simulation investigates the imaging characteristics, power attenuation patterns, and imaging features of three different GPR frequency gradients: 200 MHz, 500 MHz, and 1000 MHz. This analysis helps in selecting the appropriate detection frequency based on the observed energy attenuation patterns and imaging characteristics. Then, the model test was conducted at the selected frequency to study the penetration performance of GPR. The research results indicate that the numerical model established in this paper demonstrates good effectiveness in studying the waveform characteristics of steel fibre-reinforced concrete under various conditions. The numerical model established in this paper realized the study of the penetration characteristics and imaging features of different steel fibre contents, GPR frequencies, and detection targets. Analysis of waveform characteristics, power attenuation, and imaging results indicates that GPR at 500 MHz exhibits better detection performance for SFRC segments. The results of the numerical simulation were verified through model tests of real SFRC segments, demonstrating that 500 MHz has good penetration performance for SFRC segments. This paper also proposed a calculation method for equivalent relative dielectric constant (ERDC) based on the model test results and validated its rationality through the analysis of numerical simulation results and real GPR waveforms.

Reconstructing the Geometry of the Yushu Fault in the Tibetan Plateau Using TLS, GPR and Trenching

Although geomorphic evidence and shallow geometry of active faults are significant for the understanding and assessing of fault activity and seismic hazards, it is challenging to acquire high-resolution topographic data and shallow geometry of the Yushu fault by conventional methods. Here, we present a case study to reconstruct the detailed surficial and subsurface geometry of the Yushu fault using terrestrial laser scanning (TLS), multi-frequency ground penetrating radar (GPR) and trenching. TLS was suitable for measuring the high-resolution three-dimensional (3D) topographic data of the fault. GPR surveys with different frequency antennas (25 MHz, 100 MHz, 250 MHz and 500 MHz) were conducted to image the shallow geometry of active faults at different depths and spatial resolutions. The typical groove landscape, parallel to surface traces of the fault, was clearly observed on the TLS-derived data. A ~40 m width narrow fault system and three faults were identified on the different frequency GPR profiles. Furthermore, faults F1 and F2 were supposed to be boundary faults but were sinistral-lateral strike-slip faults with a normal component, while fault F3 was inferred as the secondary fault. The western trench section, despite the limited investigation depth (~2 m), was well consistent with the 500 MHz GPR result, especially in the location of fault F2. Finally, a 3D surficial and subsurface model was established from the TLS-derived data and GPR data offering multi-sensor and multi-view spatial data to characterize and understand the fault’s kinematics and characteristics. In addition, the shallow geometry of the fault on the GPR results would be better interpreted with the help of the corresponding surficial data. The study results demonstrate that a combination of TLS, multi-frequency GPRs and trenching can be successfully used for reconstructing a detailed surficial and subsurface geometry of the Yushu fault. It will play an increasing role in comprehensive understanding and assessing fault behavior and seismic hazards, especially on the Tibetan Plateau and the adjacent area.

Size estimation of underground targets from GPR frequency spectra: A deep learning approach

GPR (Ground Penetrating Radar) is a robust and effective device for identifying underground artefacts. Construction companies and civil engineers should be aware of the sizes of rebars and pipelines before and during construction work for various reasons. Most research efforts have typically concentrated on GPR signal analysis in the time domain, however recent studies have increasingly focused on analysis in the frequency domain. This paper proposes an artificial neural network (ANN) model for estimating the diameter of underground rods (solid) and pipes (hollow). GPR data captured in the time domain domain is transformed to the frequency domain using FFT, after which feature extraction is performed using ANN. An FPGA-based prototype GPR system is used to collect GPR A-Scan data for a variety of targets made of aluminium, stainless steel, rebar, and PVC. A mean absolute percentage error of 1.89% is achieved using the proposed model. The experimental results confirm the effectiveness of the proposed approach in extracting size-related information from GPR data.

A linear approach to simulate a constant-Q model in time-domain ground-penetrating radar modeling using multiple Debye poles: Theory and application in karst carbonate rocks

Dispersion is an important effect contributing to attenuating ground-penetrating radar (GPR) signals and must be incorporated in wave propagation. The constant-[Formula: see text] model (quality factor [Formula: see text]) is valid in rocks for typical GPR frequency ranges. In time-domain wave modeling, to simulate a constant-[Formula: see text] medium, using multiple Debye poles, the number of poles and their parameters must be previously estimated to honor target values for [Formula: see text] and velocity in the demanded frequency band. For electromagnetic waves, this problem is usually formulated as a highly nonlinear optimization problem presenting several solutions, which is solved using global optimization methods. An efficient linear approach to estimate multiple Debye poles to simulate constant-[Formula: see text] media for GPR data is presented. The resulting inverse problem is easy to solve because the number of poles is relatively small. The approach allows for a novel rescaled solution that depends only on the frequency band and number of poles. Solutions satisfying specific target values for velocity and [Formula: see text] are obtained from the rescaled solution by multiplying this solution by a proportionality factor that depends only on the target values. Choosing the number of poles is done so that velocity [Formula: see text] and [Formula: see text] curves, as a function of frequency [Formula: see text], are approximately invariant in the specified frequency band. Using the criterion that [Formula: see text] and [Formula: see text] curves must present maximum percentage deviations from the respective target values smaller than 5%, we find that, for the 200 MHz antenna, whose useful frequency band is 50–800 MHz, only three poles are sufficient. The theory is validated by modeling dispersion effects using synthetic models. The importance of introducing dispersion effects is illustrated by presenting a trial-and-error modeling approach to approximately reproduce a 200 MHz radargram acquired in fractured and karstified carbonate rocks.

Railway ballast layer inspection with different GPR antennas and frequencies

Ground penetrating radar (GPR) is a popular technology for inspecting railway ballast layer, mainly on the ballast fouling level. However, different GPR antennas with different frequencies are suitable for different inspection emphasis and diverse railway lines (weather and sub-structure). In addition, the full-scale track model (with subgrade) for experimental tests was not seen in earlier studies. For further application of GPR in China, the GPR inspections (with 400 MHz, 900 MHz and 2 GHz antennas) were performed on a 30 m long full-scale track and three railway lines (different weather and sub-structure). Results show that ballast layer inspection should be performed mainly with the 2 GHz antenna and supplemented by the 400 MHz and 900 MHz antennas. The weather has great influence on the results of GPR inspection. This study is helpful for supplementing the guidance of ballast layer inspection with GPR.

Analysis of Low-Frequency Drone-Borne GPR for Root-Zone Soil Electrical Conductivity Characterization

In this study, we analysed low-frequency drone-borne ground-penetrating radar (GPR) and full-wave inversion for soil electrical conductivity mapping. Indeed, in the lowest GPR frequency ranges, the soil surface reflexion coefficient depends more on the soil electrical conductivity than on its permittivity. Numerical experiments were conducted within the frequency range 15-45 MHz to analyse parameter sensitivities, the well-posedness of the inverse problem as well as the depth of sensitivity. The results show that the soil surface reflexion is significantly more sensitive to the soil electrical conductivity than the soil permittivity. Therefore, the conductivity can be retrieved using full-wave inversion within this frequency range, with a characterization depth varying from 0.5 to 1 m, depending on the soil properties. Yet, the permittivity also affects the results and should be accounted for in the inversion strategy. Field measurements were performed using low-frequency drone-borne radar with a 5-metre half-wave dipole antenna, and EMI measurements with different depth sensitivities were conducted for comparison. Kriging interpolation was used to get maps from measurement points. The soil conductivity maps obtained by the proposed GPR and EMI are compliant in terms of absolute values and spatial patterns. This study demonstrated the capacity of low-frequency drone-borne GPR for fast, field-scale soil electrical conductivity mapping.

Multi frequency Ground-Penetrating Radar method for mapping underground pipes and man-made objects

Mapping of subsurface infrastructure such as pipelines, pipe ducts as well as man-made objects located below the earth surface is a difficult task in geotechnical engineering due to the need to direct contact to the object. Ground-Penetrating Radar (GPR) method as one of geophysical methods is an appropriate technique to solve such problems due to its capability to effectively provide the existence, the location and the depth of buried shallow objects. Despite many advantages, the application of GPR method is limited by achieved depth and resolution range that is frequency dependent. To overcome such problems, the so-called multi-frequency compositing method with Optimal Spectral Whitening (OSW) technique is studied and applied on real data acquired in the Muarakarang Combined Cycle Power Plant area located in the Northern part of Jakarta, the Capitol of Indonesia. Datasets from GPR measurement with 100 MHz and 250 MHz was used. Each radargram from the same path was processed individually and then joined to become multiple composite radargram. The resulted composite radargram from a GPR line we studied has shown clearer image for interpretation rather than individual interpretation. The applicability of this multi-frequency compositing recommend further study to solve some facing problems in geotechnical engineering.

Numerical study of crosshole electromagnetic tunnel detection

Electromagnetic tunnel detection is studied numerically using a 3D analytic infinite lossy homogeneous space solution to magnetic dipole radiation and scattering from an infinite cylinder, in a crosshole context. At low frequencies, this serves as a model for a transmit coil radiating a time-varying magnetic field that is then detected from the open-circuit voltage induced on a receive coil. Numerical simulations illustrate how various parameters influence the signal strength and the ability to discern the scattered signal. Tunnel detection is achieved at relatively high frequencies (but below typical ground-penetrating radar frequencies) for fresh water-saturated sand and for weathered granite, which are lower loss media; for the coil and tunnel parameters used here, the optimum frequencies appear to be between 100 kHz and 1 MHz. Tunnel detection for fresh water-saturated clay, a much more lossy medium, can be achieved at a quite low frequency, with an optimum frequency between 1 and 10 kHz. These results suggest that, when a resonant coil system is used, tunnel detection may be possible in a wider range of earth media than previously reported, when the best-suited choice of frequency is used.

Geophysical monitoring of simulated clandestine burials of murder victims to aid forensic investigators

Locating murder victims buried within clandestine graves is one of the most important and difficult challenges for forensic search teams. This article details how applied geoscientists have been geophysically monitoring simulated clandestine burials, using pig cadavers as human proxies, for over 10 years, in order to discover the best geophysical methods to detect cadavers and how this might change over time. Low frequency ground penetrating radar and electrical resistivity methods could both locate the burials throughout the survey period, with winter/spring surveys producing better data and the style of burial also found to be important.

The Effect of Ground Penetrating Radar (GPR) Image Reflection on Different Pipes and Soil

Ground Penetrating Radar (GPR) works as an instrument to look for buried objects whether it is natural or man-made. GPR transmits electromagnetic (EM) wave to the ground by transmitter and the signal reflects back to the receiver. In this study, the soil characteristics were monitored based on various types of pipe underground in order to determine the reflectivity of the EM wave. Two types of pipes; iron and polyvinyl chloride (PVC) pipe were buried in two different types of soil; clay and sand. These simulations were used to monitor which type of pipe will give the most effective reflection of EM wave on that particular type of soil. The study was performed by using multiband frequency GPR of 250MHz, 400MHz, 700MHz and 900MHz. The use of multiband frequency was to identify the most suitable frequency in order to gain the most effective reflection of EM wave. The data was processed by using Reflex2DQuick software. The higher the frequency, the lower the depth penetration, but the better the resolution. The study findings showed that the power of reflectivity was high at 700MHz frequency for both pipes in both clay and sand soil types. However, the value of power reflectivity for iron pipe was higher than compared to PVC pipe at both soil textures. Meanwhile, the resolution of radargram for both pipes were much better at sand compared to clay. This information would be a helpful to the surveyors and this knowledge will make their consumed work time more efficient as they get to know more specific value of frequency that is the most suitable to gain the most effective reflection of EM wave.

Experimental Study on GPR Detection of Voids inside and behind Tunnel Linings

Ground penetrating radar (GPR) is considered an effective tool to detect tunnel lining voids. In this paper, an experimental study was carried out using a physical tunnel lining model to evaluate the performances of different antenna frequencies. We built a 4.2 m–long, 4.2 m–wide, and 2.0 m–high experimental model to simulate the secondary lining, initial lining, and surrounding rock of a tunnel structure. In the model, we created four categories of voids, which are voids in secondary and initial linings, a delamination between the secondary and initial linings, a delamination between the initial lining and sand, and a void buried in the sand, to simulate real cases in tunnel engineering. The GPR wave velocities in the sand and concrete of the model were measured using the reflection method for the calibration of void depth. We employed a commercial GPR system equipped with antennae of different centre frequencies to detect the voids. GPR data were processed using a conventional data processing flow, and the performances of different frequencies were examined. The results show that the 1000 MHz centre frequency GPR is capable of characterizing shallow buried voids in the secondary lining but is not able to penetrate into the initial lining. The 250 MHz centre frequency GPR system is not advised to detect voids in or behind tunnel linings due to its low resolving power for voids of centimetre sizes. The 500 MHz centre frequency GPR system is optimal for void detection because it demonstrated a balanced performance of resolving ability and investigation depth. The findings of this work could be useful references for antenna selection and data processing in real GPR applications.

GPR laboratory tests and numerical models to characterize cracks in cement concrete specimens, exemplifying damage in rigid pavement

Cracks in road pavements are usual damages because of heavy and dense traffic. Cracks usually are hidden to visual inspections in the case of rigid pavements. In these cases, cracked cement concrete layers are located below the asphalt layer. Therefore, detection becomes a difficult task, being only possible in the case of major damage or even failure. As consequence, rehabilitation is complex due to the technical difficulty in finding those cracks.Non-destructive surveys are in many cases applied to detect those damages. However, the difficulty in data interpretation limits their use forcing the combination of different technologies and core samples. One of the most useful method, commonly applied to define the thickness of layers, is Ground Penetrating Radar (GPR). In order to understand better the GPR images obtained as consequence of damage in the case of rigid pavement, several tests were designed to determine the ability of GPR to non-destructively detect and quantify cracks in concrete samples covered by an asphalt layer. The laboratory experiment consisted of three testing configurations: (1) one concrete sample without cracks; (2) a model of a rigid pavement with the asphalt layer without cracks; (3) the same model with different crack widths. The test was performed with a 1.6 GHz centre frequency GPR antenna in two relative positions with respect the cracks, being always the radar line perpendicular to the crack axis. These measurements allowed also evaluate the effect of orientation of the crack with respect the antenna dipoles in the GPR images. In addition, numerical models were compared to the laboratory results. The results showed that the crack width was detected in most cases, even the thinnest ones (2 mm), being the higher amplitude anomaly corresponding to the case of the data acquired with the antenna parallel to the radar line.

Interpretation of Ground Penetrating Radar Dataset using Normalised Cross-Correlation Technique

Ground Penetrating Radar (GPR) is one of the latest non-destructive geophysical technology and most widely used in detecting underground utilities. GPR can detect both metal and non-metal, however, it is unable to identify the type of underground utility object. Many researchers come out with their techniques to interpret the GPR image. The current method requires experience in interpretation. Thus, in this study, a new method to detect underground utility utilizing the Normalised Cross-Correlation (NCC) template matching technique is proposed. This technique will reduce the dependency on experts to interpret the radargram, less time consuming and eventually save cost. Upon detection, the accuracy of the system is assessed. From the accuracy assessment performed, it is shown that the system provides accurate detection results for both, depth and pipe size. The Root Mean Square Error (RMSE) for the buried pipe depth obtained by using the proposed system is 0.110 m, whereas the highest percentage match obtained is 91.34%, the remaining 8.66% mismatched might be due to the soil condition, velocity or processing parameter that affected the radargram. Based on the assessment, the developed system seems capable to detect the subsurface utility if the radar image and template image used is acquired using the same antenna frequency, point interval, and similar GPR instrument.

Recent evolution of Marmolada glacier (Dolomites, Italy) by means of ground and airborne GPR surveys

A 10-year-long evolution of ice thickness and volume of the Marmolada glacier is presented. Quantitative measurements have been performed by using two different Ground Penetrating Radar (GPR) datasets. A ground-based survey using two different ground-coupled systems equipped with 100 MHz and 35 MHz antennas was performed in 2004. In 2015 the dataset was collected by using a helicopter-borne step frequency GPR equipped with a 100 MHz antenna. Through a critical discussion of the two different methodologies, we show how both approaches are useful to estimate the ice volume within a glacier, as well as its morphological characteristics and changes with time, even if datasets are acquired in different periods of the year.The observed 2004–2014 ice volume reduction of the Marmolada glacier is equal to about 30%, while the area covered by ice decreased by about 22%. The glacier is now splitted in several separated units. It is very likely that the fragmentation of the Marmolada glacier observed in the period 2004–2014 was accelerated due to irregular karst topography. By applying the observed 2004–2014 ice-melting trend for the future although the Marmolada glacier might behave slightly differently compared to glaciers on non-karstic terrains owing to dominant vertical subglacial drainage, it will likely disappear by the year 2050. Only few isolated very small and thin ice patches will eventually survive due to avalanche feeding and shading at the foot of the north-facing cliffs.