Railway track condition assessment at network level by frequency domain analysis of GPR data

The railway track system is a crucial infrastructure for the transportation of people and goods in modern societies. With the increase in railway traffic, the availability of the track for monitoring and maintenance purposes is becoming significantly reduced. Therefore, continuous non-destructive monitoring tools for track diagnoses take on even greater importance. In this context, Ground Penetrating Radar (GPR) technique results yield valuable information on track condition, mainly in the identification of the degradation of its physical and mechanical characteristics caused by subsurface malfunctions. Nevertheless, the application of GPR to assess the ballast condition is a challenging task because the material electromagnetic properties are sensitive to both the ballast grading and water content. This work presents a novel approach, fast and practical for surveying and analysing long sections of transport infrastructure, based mainly on expedite frequency domain analysis of the GPR signal. Examples are presented with the identification of track events, ballast interventions and potential locations of malfunctions. The approach, developed to identify changes in the track infrastructure, allows for a user-friendly visualisation of the track condition, even for GPR non-professionals such as railways engineers, and may further be used to correlate with track geometric parameters. It aims to automatically detect sudden variations in the GPR signals, obtained with successive surveys over long stretches of railway lines, thus providing valuable information in asset management activities of infrastructure managers

Ground‐Penetrating Radar for Close‐in Mine Detection

In this chapter, two of the major challenges in the application of ground‐penetrating radar in humanitarian demining operations are addressed: (i) development and testing of affordable and practical ground penetrating radar (GPR)‐based systems, which can be used off‐ground and (ii) development of robust signal processing techniques for landmines detection and identification. Different approaches developed at the Royal Military Academy in order to demonstrate the possibility of enhancing close‐range landmine detection and identification using ground‐penetrating radar under laboratory and outdoor conditions are summarized here. Data acquired using different affordable and practical GPR‐based systems are used to validate a number of promising developments in signal processing techniques for target detection and identification. The proposed approaches have been validated with success in laboratory and outdoor conditions and for different scenarios, including antipersonnel, low‐metal content landmines, improvised explosive devices and real mine‐affected soils

An evaluation of the performance of multi-static handheld ground penetrating radar using full wave inversion for landmine detection

This thesis presents an empirical study comparing the ability of multi-static and bi-static, handheld, ground penetrating radar (GPR) systems, using full wave inversion (FWI), to determine the properties of buried anti-personnel (AP) landmines. A major problem associated with humanitarian demining is the occurrence of many false positives during clearance operations. Therefore, a reduction of the false alarm rate (FAR) and/or increasing the probability of detection (POD) is a key research and technical objective. Sensor fusion has emerged as a technique that promises to significantly enhance landmine detection. This study considers a handheld, combined metal detector (MD) and GPR device, and quantifies the advantages of the use of antenna arrays. During demining operations with such systems, possible targets are detected using the MD and further categorised using the GPR, possibly excluding false positives. A system using FWI imaging techniques to estimate the subsurface parameters is considered in this work.A previous study of multi-static GPR FWI used simplistic, 2D far-field propagation models, despite the targets being 3D and within the near field. This novel study uses full 3D electromagnetic (EM) wave simulation of the antenna arrays and propagation through the air and ground. Full EM simulation allows the sensitivity of radio measurements to landmine characteristics to be determined. The number and configuration of antenna elements are very important and must be optimised, contrary to the 2D sensitivity studies in (Watson, Lionheart 2014, Watson 2016) which conclude that the degree (number of elements) of the multi-static system is not critical. A novel sensitivity analysis for tilted handheld GPR antennas is used to demonstrate the positive impact of tilted antenna orientation on detection performance. A time domain GPR and A-scan data, consistent with a commercial handheld system, the MINEHOUND, is used throughout the simulated experiments which are based on synthetic GPR measurements.Finally, this thesis introduces a novel method of optimising the FWI solution through feature extraction or estimation of the internal air void typically present in pressure activated mines, to distinguish mines from non-mine targets and reduce the incidence of false positives

Advanced Techniques for Ground Penetrating Radar Imaging

Ground penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in non-destructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR for NDT has been successfully introduced in a wide range of sectors, such as mining and geology, glaciology, civil engineering and civil works, archaeology, and security and defense. In recent decades, improvements in georeferencing and positioning systems have enabled the introduction of synthetic aperture radar (SAR) techniques in GPR systems, yielding GPR–SAR systems capable of providing high-resolution microwave images. In parallel, the radiofrequency front-end of GPR systems has been optimized in terms of compactness (e.g., smaller Tx/Rx antennas) and cost. These advances, combined with improvements in autonomous platforms, such as unmanned terrestrial and aerial vehicles, have fostered new fields of application for GPR, where fast and reliable detection capabilities are demanded. In addition, processing techniques have been improved, taking advantage of the research conducted in related fields like inverse scattering and imaging. As a result, novel and robust algorithms have been developed for clutter reduction, automatic target recognition, and efficient processing of large sets of measurements to enable real-time imaging, among others. This Special Issue provides an overview of the state of the art in GPR imaging, focusing on the latest advances from both hardware and software perspectives

Efficient Underground Object Detection for Ground Penetrating Radar Signals

Ground penetrating radar (GPR) is one of the common sensor system for underground inspection. GPR emits electromagnetic waves which can pass through objects. The reflecting waves are recorded and digitised, and then, the B-scan images are formed. According to the properties of scanning object, GPR creates higher or lower intensity values on the object regions. Thus, these changes in signal represent the properties of scanning object. This paper proposes a 3-step method to detect and discriminate landmines: n-row average-subtraction (NRAS); Min-max normalisation; and image scaling. Proposed method has been tested using 3 common algorithms from the literature. According to the results, it has increased object detection ratio and positive object discrimination (POD) significantly. For artificial neural networks (ANN), POD has increased from 77.4 per cent to 87.7 per cent. And, it has increased from 37.8 per cent to 80.2 per cent, for support vector machines (SVM)

Modern GPR Target Recognition Methods

Traditional GPR target recognition methods include pre-processing the data by removal of noisy signatures, dewowing (high-pass filtering to remove low-frequency noise), filtering, deconvolution, migration (correction of the effect of survey geometry), and can rely on the simulation of GPR responses. The techniques usually suffer from the loss of information, inability to adapt from prior results, and inefficient performance in the presence of strong clutter and noise. To address these challenges, several advanced processing methods have been developed over the past decade to enhance GPR target recognition. In this chapter, we provide an overview of these modern GPR processing techniques. In particular, we focus on the following methods: adaptive receive processing of range profiles depending on the target environment; adoption of learning-based methods so that the radar utilizes the results from prior measurements; application of methods that exploit the fact that the target scene is sparse in some domain or dictionary; application of advanced classification techniques; and convolutional coding which provides succinct and representatives features of the targets. We describe each of these techniques or their combinations through a representative application of landmine detection.Comment: Book chapter, 56 pages, 17 figures, 12 tables. arXiv admin note: substantial text overlap with arXiv:1806.0459

Investigating Key Techniques to Leverage the Functionality of Ground/Wall Penetrating Radar

Ground penetrating radar (GPR) has been extensively utilized as a highly efficient and non-destructive testing method for infrastructure evaluation, such as highway rebar detection, bridge decks inspection, asphalt pavement monitoring, underground pipe leakage detection, railroad ballast assessment, etc. The focus of this dissertation is to investigate the key techniques to tackle with GPR signal processing from three perspectives: (1) Removing or suppressing the radar clutter signal; (2) Detecting the underground target or the region of interest (RoI) in the GPR image; (3) Imaging the underground target to eliminate or alleviate the feature distortion and reconstructing the shape of the target with good fidelity. In the first part of this dissertation, a low-rank and sparse representation based approach is designed to remove the clutter produced by rough ground surface reflection for impulse radar. In the second part, Hilbert Transform and 2-D Renyi entropy based statistical analysis is explored to improve RoI detection efficiency and to reduce the computational cost for more sophisticated data post-processing. In the third part, a back-projection imaging algorithm is designed for both ground-coupled and air-coupled multistatic GPR configurations. Since the refraction phenomenon at the air-ground interface is considered and the spatial offsets between the transceiver antennas are compensated in this algorithm, the data points collected by receiver antennas in time domain can be accurately mapped back to the spatial domain and the targets can be imaged in the scene space under testing. Experimental results validate that the proposed three-stage cascade signal processing methodologies can improve the performance of GPR system

Techniques for improving landmine detection using ground penetrating radar

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file viewed on (February 23, 2007)Includes bibliographical references.Thesis (M.S.) University of Missouri-Columbia 2006.Dissertations, Academic -- University of Missouri--Columbia -- Electrical engineering.Improving the probability of detection of landmines is a challenging task for many scientists all around the world. The goal of this research is to be a part of this challenging work to investigate techniques for landmine detection. Two techniques for detecting the landmines, one in depth domain and the other in frequency domain, have been studied and a few modifications are suggested, along with the results. The data collected from Ground Penetrating Radar (GPR) from various test sites is used to evaluate the performance of these detection techniques. The first technique is proposed for use with Handheld GPR systems, while the second technique is proposed for use with Vehicle mounted GPR systems. The techniques proved to be useful in improving the detection of low metal or plastic mines

Guidebook on Detection Technologies and Systems for Humanitarian Demining

The aim of this publication is to provide the mine action community, and those supporting mine action, with a consolidated review and status summary of detection technologies that could be applied to humanitarian demining operations. This Guidebook is meant to provide information to a wide variety of readers. For those not familiar with the spectrum of technologies being considered for the detection of landmines and for area reduction, there is a brief overview of the principle of operation for each technology as well as a summary listing of the strengths, limitations, and potential for use of the technology to humanitarian demining. For those with an intermediate level of understanding for detection technologies, there is information regarding some of the more technical details of the system to give an expanded overview of the principles involved and hardware development that has taken place. Where possible, technical specifications for the systems are provided. For those requiring more information for a particular system, relevant publications lists and contact information are also provided