Multi-perspective high range resolution profiles of landmines

Landmine clearance is a severe and unresolved humanitarian issue. The development of low-cost, smaller, faster and lighter Ground Penetrating Radars (GPR), which can be mounted on unmanned platforms, will allow faster and safer 24/7 operations. This technology will make it possible to survey affected areas with more flexible trajectories and these will provide measurements of landmine signatures from many different aspect angles. As a result, multi-perspective information over wide angular windows and the behaviour of the signature as a function of the angle of illumination can be exploited. Landmine signatures are expected to present features that are less sensitive to the angle of illumination with respect to those of common cluttered objects, and this can lead to an improvement in detection and discrimination performance. In this paper, we present the results of an experimental trial carried out to collect the High Range Resolution Profiles (HRRPs) of two landmines, the SB-33 and the VS-50, off the ground. An analysis of the auto-correlation function of each range bin as a function of the aspect angle is presented together with that of the cross-correlation between profiles collected from different aspect angles

Clutter removal of near-field UWB SAR imaging for pipeline penetrating radar

Recently, ultrawideband (UWB) near-field synthetic aperture radar (SAR) imaging has been proposed for pipeline penetrating radar applications thanks to its capability in providing suitable resolution and penetration depth. Because of geometrical restrictions, there are many complicated sources of clutter in the pipe. However, this issue has not been investigated yet. In this article, we investigate some well-known clutter removal algorithms using full-wave simulated data and compare their results considering image quality, signal to clutter ratio and contrast. Among candidate algorithms, two-dimensional singular spectrum analysis (2-D SSA) shows a good potential to improve the signal to clutter ratio. However, basic 2-D SSA produces some artifacts in the image. Therefore, to mitigate this issue, we propose “modified 2-D SSA.” After developing the suitable clutter removal algorithm, wepropose a complete algorithm chain for pipeline imaging. An UWB nearfieldSARmonitoring system including anUWBM-sequence sensor and automatic positioner are implemented and the image of drilled perforations in a concrete pipe mimicking oil well structure as a case study is reconstructed to test the proposed algorithm. Compared to the literature, a comprehensive near-field SAR imaging algorithm including new clutter removal is proposed and its performance is verified by obtaining high-quality images in experimental results

Investigation of Time-Frequency Features for GPR Landmine Discrimination

科研費報告書収録論文(課題番号:14102024/研究代表者:佐藤源之/ポーラリメトリック・インターフェロメトリックレーダによる地雷検知に関する研究

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

Design and Applications of Multi-Frequency Holographic Subsurface Radar: Review and Case Histories

Holographic subsurface radar (HSR) is not currently in widespread usage. This is due to a historical perspective in the ground-penetrating radar (GPR) community that the high attenuation of electromagnetic waves in most media of interest and the inability to apply time-varying gain to the continuous-wave (CW) HSR signal preclude sufficient effective penetration depth. While it is true that the fundamental physics of HSR, with its use of a CW signal, does not allow amplification of later (i.e., deeper) arrivals in lossy media (as is possible with impulse subsurface radar (ISR)), HSR has distinct advantages. The most important of these is the ability to do shallow subsurface imaging with a resolution that is not possible with ISR. In addition, the design of an HSR system is simpler than for ISR due to the relatively low-tech transmitting and receiving antennae. This paper provides a review of the main principles of HSR through an optical analogy and describes possible algorithms for radar hologram reconstruction. We also present a review of the history of development of systems and applications of the RASCAN type, which is possibly the only commercially available holographic subsurface radar. Among the subsurface imaging and remote sensing applications considered are humanitarian demining, construction inspection, nondestructive testing of dielectric aerospace materials, surveys of historic architecture and artworks, paleontology, and security screening. Each application is illustrated with relevant data acquired in laboratory and/or field experiments

Modulation techniques for GPR system radargram

Ground Penetrating Radar (GPR) system ability to detect embedded object underground is dependent on the ultra-wideband antenna use. Based on this antenna type, the fractional bandwidth used by the GPR system is usually greater or equal to 1. On the other hand, the GPR system using fractional bandwidth less than 1 will produce unsmooth GPR radargram, as the consequences of high signal ripples generated in the system output signals. Based on fractional bandwidth parameter, this study focuses in developing a digital signal processing of the GPR system to produce a smooth GPR radargram. The proposed GPR signal processing system is based on envelope detector technique of Asynchronous Half-Wave (AHW), Asynchronous Full-Wave (AFW) and Asynchronous Real Square Law (ARSL). The Pulse Modulation (PM), Stepped Frequency Continuous Wave (SFCW) and Hybrid GPR system simulation are modeled using CST Studio Suite and MATLAB software. The selected fractional bandwidth of the GPR system simulation modeled is 0.46 and 0.4 for Microstrip Vivaldi and Horn antennas respectively. In addition, a practical implementation of the SFCW and Hybrid GPR system using fabricated Microstrip Vivaldi antenna having a fractional bandwidth of 0.46 and VNA equipment, was conducted. Based on the analysis results of the proposed PM GPR system simulation, the AFW technique produces clearer PM GPR radargram. The detection rate for PM GPR system simulation using AFW technique is 87% and 51.3% using Horn and Microstrip Vivaldi antennas respectively. Practical implementation of SFCW and Hybrid GPR systems using AFW technique and Microstrip Vivaldi antenna can detect an iron and a bottle filled with water object

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

Measurement of snow water equivalent using drone-mounted ultra-wide-band radar

The use of unmanned aerial vehicle (UAV)-mounted radar for obtaining snowpack parameters has seen considerable advances over recent years. However, a robust method of snow density estimation still needs further development. The objective of this work is to develop a method to reliably and remotely estimate snow water equivalent (SWE) using UAV-mounted radar and to perform initial field experiments. In this paper, we present an improved scheme for measuring SWE using ultra-wide-band (UWB) (0.7 to 4.5 GHz) pseudo-noise radar on a moving UAV, which is based on airborne snow depth and density measurements from the same platform. The scheme involves autofocusing procedures with the frequency–wavenumber (F–K) migration algorithm combined with the Dix equation for layered media in addition to altitude correction of the flying platform. Initial results from field experiments show high repeatability (R > 0.92) for depth measurements up to 5.5 m, and good agreement with Monte Carlo simulations for the statistical spread of snow density estimates with standard deviation of 0.108 g/cm3. This paper also outlines needed system improvements to increase the accuracy of a snow density estimator based on an F–K migration technique