10th International Workshop on Advanced Ground Penetrating Radar

In this article, we propose a new design we call the “Gopher antenna”: a patch antenna structure which does not require a resistive load and is therefore more efficient than the current ground-penetrating radar (GPR) antennas. When tested, it works well in a GPR application as low as approximately -25 dB of the application’s original transmit power. The Gopher antenna also meets the general requirements for the GPR antennas: a received wide spectrum and a good impulse response. Departing from the common designs (bow-tie dipoles and horn/Vivaldi structures), the Gopher antenna is a patch-antenna structure consisting of a quarter-wave feeder and a parasitic half-wave patch with no resistive load. The Gopher antenna has a directive radiation pattern, a good impulse response without distortion, a reasonable cross-polarization ratio, and a good radiated spectrum also when placed on the ground.

This paper presents the results of a Ground Penetrating Radar survey on a historical building taking part of the “Bellariva” sport Centre, designed and built in Florence (Italy) in 1957-1960 years by the Word-famous Italian engineer Pier Luigi Nervi. The building under survey hosts the locker rooms of the swimming pool and a bar at the first floor, a restaurant at the second where an evident crack was observed. A Ground Penetrating Radar survey was performed in order to determinate the internal structure of the floor, dimensions and disposition of steel bars, and to gather information about the connections between perimeter beams and balcony at the level of the restaurant. The survey confirmed what were reported on the original drawings of the building. The results of the survey will be used for defining a numerical model and to design possible retrofit interventions.

In this contribution, a multidisciplinary investigation regarding the Roman Amphitheatre in Lecce, southern Italy, is be proposed. In particular, GPR prospecting combined to passive seismic measurements and with a virtual reconstruction of the monument allows deducing some important features of the monument, unknown before. In particular, this is a monument only partially brought to light, and part of it lies under the current Saint Oronzo’s Square. We have investigated about the part still undiscovered of the amphitheatre.

An increasing number of Ground-Penetrating Radar (GPR) studies takes benefit from illumination capabilities provided by dense acquisitions between boreholes. Traveltime tomography, migration and full waveform inversion provide high-resolution images to be interpreted. Tomography is often performed under an isotropic assumption, although anisotropy may exist at different scales. A new tomography approach is investigated based on an anisotropic Eikonal solver for the forward problem and an adjoint formulation for inverse problem. The misfit gradient is computed directly without expressing the sensitivity matrix, leading to explicit contribution of anisotropic parameters. The parametrization of elliptical anisotropy based on vertical and horizontal velocities is preferred to a parametrization based on Thomsen parameters for a realistic synthetic example, inspired from a real example of GPR transmission tomography between two boreholes in a carbonate environment where an old gallery exists. The vertical velocity is nicely recovered while the anisotropy contribution stays small. However, the real application provides similar results either through a layered isotropic model or through a smoother anisotropic model. Geological information is, therefore, needed for further specific interpretation.

Coarse roots can cause damage to pipes, pavements and building foundations. Hence, reconstructing tree root system in its three dimensions is of paramount importance to understand and reduce interactions between trees and urban infrastructures. Ground Penetrating Radar (GPR) is a promising non-invasive technique for the study of tree roots. In this contribution, a 3D GPR simulation was carried out on two roots having elemental architectures in order to be reconstructed. The simulation was performed with GprMax software under heterogeneous soil conditions. Considering a heterogeneous soil not only provided a realistic soil model, but also enabled us to test the robustness of our post-processing techniques. We mainly used a Singular Value Decomposition (SVD) combined with the matched filter technique.

Iran and Italy have a great potential in stone production relying on a variety of dimension stone quarries, especially carbonate rocks. To survive in the modern challenging international market, it is crucial to have products without defects. Ground Penetrating Radar (GPR) method as a rapid and efficient non-destructive technique (NDT) can be used to characterize carbonate rocks during different production stages. In this paper, we present the results of GPR measurements to monitor the quality of marble and limestone rocks at different scales. Considering the availability of GPR antennas in a wide range of frequencies, providing different resolutions, GPR method is very encouraging to detect the desired discontinuities of carbonate rocks at different production stages. Lower frequency antennas can detect major discontinuities to optimize the extraction design. Higher frequency antennas can later detect smaller fractures of the extracted blocks to optimize slab production. Our research is under progress to explore the efficiency of GPR method in mapping the quality of resin injection in fractured rocks. As an auxiliary NDT method to be integrated with GPR measurements, ultrasonic pulse velocity tests are also performed. The results show that changes in the velocity can be a good indication of the stone quality.

Main damage occurring on reinforced concrete (RC) structures can be attributed to the corrosion of the rebar. When dealing with structures in marine environment, chloride ion penetration and water content must be considered, as the different exposure zones (tidal, splash and atmospheric) will have a significant influence.

GPR survey were performed on several piles and processed to evaluate the evolution of the surface permitivity vs. elevation in the tidal and splash areas. For that, a in-house software by HK Polytechnic university was used to estimate the local radar wave velocity for each location of rebar. The objective herein is to estimate if any vertical gradient of water/chloride content in the surface content. GPR results show a notable decrease of water content between the tidal and the atmospheric area, and no significant information on any gradient of chloride content vs. elevation.

This paper presents a software tool which simulates the geological stratigraphy of a potash mine which is then used with gprMax (public domain Ground Penetrating Radar (GPR) simulation software) to examine and evaluate the effectiveness of auto-picking algorithms. The system is used to simulate the GPR response from clay seams in the roof of potash mining rooms. As it is extremely onerous to obtain in-situ data that captures all possible normal and anomalous geological conditions present in the mine roof, earth models are generated which accurately represents the geology of the mine. In particular, random clays in the mine roof can negatively affect the performance of auto-picking algorithms. These earth model simulations can be used to present these random clays accurately.

gprMax is an open source software that simulates Electro-Magnetic (EM) wave propagation in materials in order to support a better understanding of the use of GPR in various applications. Currently, GPR systems are in use in potash mines to assist with monitoring of the roof status of mining rooms. The goal of this paper is to validate the ability of using gprMax with effective earth models to generate realistic GPR signals that are used to test and evaluate auto-picking algorithms. The use of simulated data in comparison to the experimental (actual physical) data and generation of test bed models for an auto-picking algorithm has many benefits. Synthetic data is generated by gprMax using the Finite Difference Time Domain (FDTD) methodology. An effective methodology to develop and test robust auto-picking algorithms is created using simulated GPR signals because the ground truth is known from the earth models.

Additionally, in this work results from both an industry standard auto-picking algorithm and a newly developed auto-picking algorithm, called Clustered Ratio Derivative (CRD), are presented for this mine roof monitoring application. Finally, in this work we take advantage of cloud computing resources in order to execute this work.

In this work we consider the problem of developing algorithms for automatic buried threat detection (BTD) in ground penetrating radar (GPR) data. Many such algorithms are supervised, and perform best when they can be trained on large quantities of labeled threat and non-threat GPR data, respectively. Unfortunately, such data is costly to collect, and therefore relatively scarce. One approach to mitigate this problem is data augmentation, in which novel training data is created by applying transformations to existing data. Prior work has shown that augmentation can indeed improve the training of GPR-based BTD algorithms. In this work, we explore the use of Generative Adversarial Networks (GANs) for data augmentation. GANs can be trained to generate novel, but highly realistic, data after training on a real-world dataset. GANs have yielded impressive results on many types of data, but they are notoriously difficult to train. In this work, we propose an approach, entitled featureGAN, that mitigates some of the challenges training GANs. We show that augmentation using featureGAN yields improved detection performance, and yields better performance than some naïve alternative augmentation strategies. We also propose a metric for quantifying the success of GAN training, called the q-metric, which was crucial to achieving good results.