SPOT-GPR: a freeware tool for target detection and localizationin GPR data developed within the COST action TU1208

SPOT-GPR (release 1.0) is a new freeware tool implementing an innovative Sub-Array Processing method, for the analysis of Ground-Penetrating Radar (GPR) data with the main purposes of detecting and localizing targets. The software is implemented in Matlab, it has a graphical user interface and a short manual. This work is the outcome of a series of three Short-Term Scientific Missions (STSMs) funded by European COoperation in Science and Technology (COST) and carried out in the framework of the COST Action TU1208 “Civil Engineering Applications of Ground Penetrating Radar” (www.GPRadar.eu). The input of the software is a GPR radargram (B-scan). The radargram is partitioned in subradargrams, composed of a few traces (A-scans) each. The multi-frequency information enclosed in each trace is exploited and a set of dominant Directions of Arrival (DoA) of the electromagnetic field is calculated for each sub-radargram. The estimated angles are triangulated, obtaining a pattern of crossings that are condensed around target locations. Such pattern is filtered, in order to remove a noisy background of unwanted crossings, and is then processed by applying a statistical procedure. Finally, the targets are detected and their positions are predicted. For DoA estimation, the MUltiple SIgnal Classification (MUSIC) algorithm is employed, in combination with the matched filter technique. To the best of our knowledge, this is the first time the matched filter technique is used for the processing of GPR data. The software has been tested on GPR synthetic radargrams, calculated by using the finite-difference timedomain simulator gprMax, with very good results

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

The design of hardware and signal processing for a stepped frequency continuous wave ground penetrating radar

Includes bibliographical references.A Ground Penetrating Radar (GPR) sensor is required to provide information that will allow the user to detect, classify and identify the target. This is an extremely tough requirement, especially when one considers the limited amount of information provided by most GPRs to accomplish this task. One way of increasing this information is to capture the complete scattering matrix of the received radar waveform. The objective of this thesis is to develop a signal processing technique to extract polarimetric feature vectors from Stepped Frequency Continuous Wave (SFGWV) GPR data. This was achieved by first developing an algorithm to extract the parameters from single polarization SFCW GPR data and then extending this algorithm to extract target features from fully polarimetric data. A model is required to enable the extraction of target parameters from raw radar data. A single polarization SFCW GPR model is developed based on the radar geometry and linear approximations to the wavenumber in a lossy medium. Assuming high operating frequencies and/or low conductive losses, the model is shown to be equivalent to the exponential model found in signal processing theory. A number of algorithms exist to extract the required target parameters from the measured data in a least squared sense. In this thesis the Matrix Pencil-of-Function Method is used. Numerical simulations are presented to show the performance of this algorithm for increasing model error. Simulations are also provided to compare the standard Inverse Discrete Fourier Transform (IDFT) with the algorithm presented in this thesis. The processing is applied to two sets of measured radar data using the radar developed in the thesis. The technique was able to locate the position of the scatterers for both sets of data, thus demonstrating the success of the algorithm on practical measurements. The single polarization model is extended to a fully polarimetric SFCW GPR model. The model is shown to relate to the multi-dimensional exponential signal processing model, given certain assumptions about the target scattering damping factor. The multi-snapshot Matrix Pencil-of-Function Method is used to extract the scattering matrix parameters from the raw polarimetric stepped frequency data. Those Huynen target parameters that are independent of the properties of the medium, are extracted from the estimated scattering matrices. Simulations are performed to examine the performance of the algorithm for increasing conductive and dielectric losses. The algorithm is also applied to measured data for a number of targets buried a few centimeters below the ground surface, with promising results. Finally, the thesis describes the design and development of a low cost, compact and low power SFCW GPR system. It addresses both the philosophy as well as the technology that was used to develop a 200 - 1600 MHz and a 1 - 2 GHz system. The system is built around a dual synthesizer heterodyne architecture with a single intermediate frequency stage and a novel coherent demodulator system - with a single reference source. Comparison of the radar system with a commercial impulse system, shows that the results are of a similar quality. Further measurements demonstrate the radar performance for different field test cases, including the mapping of the bottom of an outdoor test site down to 1.6 m

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

Performance Analysis of Tomographic Methods against Experimental Contactless Multistatic Ground Penetrating Radar

Ground-penetrating radar (GPR) technology for underground exploration consists of the transmission of an electromagnetic signal in the ground for sensing the presence of buried objects. While monostatic or bistatic configurations are usually adopted, a limited number of multistatic GPR systems have been proposed in the scientific literature. In this article, we investigate the recovery performance of a specific and unconventional contactless multistatic GPR system, designed at the Georgia Institute of Technology for the subsurface imaging of antitank and antipersonnel plastic mines. In particular, for the first time, tomographic approaches are tested against this experimental multistatic GPR system, while most GPR processing in the scientific literature processes multimonostatic experimental data sets. First, by mimicking the system at hand, an accurate theoretical as well as numerical analysis is performed in order to estimate the data information content and the performance achievable. Two different tomographic linear approaches are adopted, i.e., the linear sampling method and the Born approximation (BA) method, this latter enhanced by means of the compressive sensing (CS) theoretical framework. Then, the experimental data provided by the Georgia Institute of Technology are processed by means of a multifrequency CS- and BA-based method, thus generating very accurate 3D maps of the investigated underground scenario

Radar Technology

In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design