スパースアレイ・レーダにおける信号処理技術

Tohoku University佐藤源之課

Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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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

The emergence of hydrogeophysics for improved understanding of subsurface processes over multiple scales

Geophysics provides a multi-dimensional suite of investigative methods that are transforming our ability to see into the very fabric of the subsurface environment, and monitor the dynamics of its fluids and the biogeochemical reactions that occur within it. Here, we document how geophysical methods have emerged as valuable tools for investigating shallow subsurface processes over the past two decades and offer a vision for future developments relevant to hydrology and also ecosystem science. The field of “hydrogeophysics” arose in the late 1990s, prompted, in part, by the wealth of studies on stochastic subsurface hydrology that argued for better field-based investigative techniques. These new hydrogeophysical approaches benefited from the emergence of practical and robust data inversion techniques, in many cases with a view to quantify shallow subsurface heterogeneity and the associated dynamics of subsurface fluids. Furthermore, the need for quantitative characterization stimulated a wealth of new investigations into petrophysical relationships that link hydrologically relevant properties to measurable geophysical parameters. Development of time-lapse approaches provided a new suite of tools for hydrological investigation, enhanced further with the realization that some geophysical properties may be sensitive to biogeochemical transformations in the subsurface environment, thus opening up the new field of “biogeophysics”. Early hydrogeophysical studies often concentrated on relatively small ‘plot-scale’ experiments. More recently, however, the translation to larger-scale characterization has been the focus of a number of studies. Geophysical technologies continue to develop, driven, in part, by the increasing need to understand and quantify key processes controlling sustainable water resources and ecosystem services

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

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

Integrated Ground Penetrating Radar (GPR) imaging and characterization of glacial and periglacial environments

This PhD research is based on Ground Penetrating Radar (GPR) imaging and characterization of glacial and periglacial environments. Its main focus is the assessment of the physical meaning of electromagnetic (EM) facies of frozen materials, proving that a detailed analysis of the geophysical data and often the integration with other prospecting techniques is essential because inferences on some kind of facies could not be clearly unambiguous. Chapters 2 and 3 of this dissertation present the characterization of a high scattered facies within an ice body, which was proved to be not straightforwardly related to warm ice and the presence of liquid water, as usually occurs in GPR data. An investigation approach based on differential diagnosis of the information obtained by different techniques (as GPR, photogrammetry, geomorphology) was proposed, representing something completely new for geophysical applications. Once such a facies was related to englacial debris within the ice, GPR modelling and inversion were fundamental to provide a first quantification of the debris causing the high scattered zone through a scattering amplitude inversion approach based on the combined analysis of synthetic and field data. It resulted that just a percentage below 10% in volume can produce the high scattered facies imaged on GPR data. A second focus of the research, arising from the main one, gets the issue of the ambiguity of the interpretation, the integration of techniques and the role of debris in a glacial body for improving both the characterization of an Alpine glacier and the geometrical imaging of Antarctic environments. The outcome of these researches, which are still ongoing, points out the relation between some surficial structures and the subsurface, revealing much more complex settings than expected just from geomorphological analysis and local drilling. As a matter of fact, this research deepened the knowledge in the identification of peculiar EM facies, including dead ice patches, and morphologies which affect the occurrence of periglacial elements and mixed glacial and fluvio-glacial features. Such research allowed to develop dedicated and new methodology of data analysis, considering GPR attribute analysis, differential diagnosis and the scattering amplitude approach for GPR inversion. The outcomes reached through this research are innovative, as they open new research possibilities and define the road ahead not only for future GPR glaciological researches, but also for different practical applications.This PhD research is based on Ground Penetrating Radar (GPR) imaging and characterization of glacial and periglacial environments. Its main focus is the assessment of the physical meaning of electromagnetic (EM) facies of frozen materials, proving that a detailed analysis of the geophysical data and often the integration with other prospecting techniques is essential because inferences on some kind of facies could not be clearly unambiguous. Chapters 2 and 3 of this dissertation present the characterization of a high scattered facies within an ice body, which was proved to be not straightforwardly related to warm ice and the presence of liquid water, as usually occurs in GPR data. An investigation approach based on differential diagnosis of the information obtained by different techniques (as GPR, photogrammetry, geomorphology) was proposed, representing something completely new for geophysical applications. Once such a facies was related to englacial debris within the ice, GPR modelling and inversion were fundamental to provide a first quantification of the debris causing the high scattered zone through a scattering amplitude inversion approach based on the combined analysis of synthetic and field data. It resulted that just a percentage below 10% in volume can produce the high scattered facies imaged on GPR data. A second focus of the research, arising from the main one, gets the issue of the ambiguity of the interpretation, the integration of techniques and the role of debris in a glacial body for improving both the characterization of an Alpine glacier and the geometrical imaging of Antarctic environments. The outcome of these researches, which are still ongoing, points out the relation between some surficial structures and the subsurface, revealing much more complex settings than expected just from geomorphological analysis and local drilling. As a matter of fact, this research deepened the knowledge in the identification of peculiar EM facies, including dead ice patches, and morphologies which affect the occurrence of periglacial elements and mixed glacial and fluvio-glacial features. Such research allowed to develop dedicated and new methodology of data analysis, considering GPR attribute analysis, differential diagnosis and the scattering amplitude approach for GPR inversion. The outcomes reached through this research are innovative, as they open new research possibilities and define the road ahead not only for future GPR glaciological researches, but also for different practical applications

Enhancing the information content of geophysical data for nuclear site characterisation

Our knowledge and understanding to the heterogeneous structure and processes occurring in the Earth’s subsurface is limited and uncertain. The above is true even for the upper 100m of the subsurface, yet many processes occur within it (e.g. migration of solutes, landslides, crop water uptake, etc.) are important to human activities. Geophysical methods such as electrical resistivity tomography (ERT) greatly improve our ability to observe the subsurface due to their higher sampling frequency (especially with autonomous time-lapse systems), larger spatial coverage and less invasive operation, in addition to being more cost-effective than traditional point-based sampling. However, the process of using geophysical data for inference is prone to uncertainty. There is a need to better understand the uncertainties embedded in geophysical data and how they translate themselves when they are subsequently used, for example, for hydrological or site management interpretations and decisions. This understanding is critical to maximize the extraction of information in geophysical data. To this end, in this thesis, I examine various aspects of uncertainty in ERT and develop new methods to better use geophysical data quantitatively. The core of the thesis is based on two literature reviews and three papers. In the first review, I provide a comprehensive overview of the use of geophysical data for nuclear site characterization, especially in the context of site clean-up and leak detection. In the second review, I survey the various sources of uncertainties in ERT studies and the existing work to better quantify or reduce them. I propose that the various steps in the general workflow of an ERT study can be viewed as a pipeline for information and uncertainty propagation and suggested some areas have been understudied. One of these areas is measurement errors. In paper 1, I compare various methods to estimate and model ERT measurement errors using two long-term ERT monitoring datasets. I also develop a new error model that considers the fact that each electrode is used to make multiple measurements. In paper 2, I discuss the development and implementation of a new method for geoelectrical leak detection. While existing methods rely on obtaining resistivity images through inversion of ERT data first, the approach described here estimates leak parameters directly from raw ERT data. This is achieved by constructing hydrological models from prior site information and couple it with an ERT forward model, and then update the leak (and other hydrological) parameters through data assimilation. The approach shows promising results and is applied to data from a controlled injection experiment in Yorkshire, UK. The approach complements ERT imaging and provides a new way to utilize ERT data to inform site characterisation. In addition to leak detection, ERT is also commonly used for monitoring soil moisture in the vadose zone, and increasingly so in a quantitative manner. Though both the petrophysical relationships (i.e., choices of appropriate model and parameterization) and the derived moisture content are known to be subject to uncertainty, they are commonly treated as exact and error‐free. In paper 3, I examine the impact of uncertain petrophysical relationships on the moisture content estimates derived from electrical geophysics. Data from a collection of core samples show that the variability in such relationships can be large, and they in turn can lead to high uncertainty in moisture content estimates, and they appear to be the dominating source of uncertainty in many cases. In the closing chapters, I discuss and synthesize the findings in the thesis within the larger context of enhancing the information content of geophysical data, and provide an outlook on further research in this topic

Ice Shelf Melt Rates and 3D Imaging

Ice shelves are sensitive indicators of climate change and play a critical role in the stability of ice sheets and oceanic currents. Basal melting of ice shelves plays an important role in both the mass balance of the ice sheet and the global climate system. Airborne- and satellite based remote sensing systems can perform thickness measurements of ice shelves. Time separated repeat flight tracks over ice shelves of interest generate data sets that can be used to derive basal melt rates using traditional glaciological techniques. Many previous melt rate studies have relied on surface elevation data gathered by airborne- and satellite based altimeters. These systems infer melt rates by assuming hydrostatic equilibrium, an assumption that may not be accurate, especially near an ice shelf’s grounding line. Moderate bandwidth, VHF, ice penetrating radar has been used to measure ice shelf profiles with relatively coarse resolution. This study presents the application of an ultra wide bandwidth (UWB), UHF, ice penetrating radar to obtain finer resolution data on the ice shelves. These data reveal significant details about the basal interface, including the locations and depth of bottom crevasses and deviations from hydrostatic equilibrium. While our single channel radar provides new insight into ice shelf structure, it only images a small swatch of the shelf, which is assumed to be an average of the total shelf behavior. This study takes an additional step by investigating the application of a 3D imaging technique to a data set collected using a ground based multi channel version of the UWB radar. The intent is to show that the UWB radar could be capable of providing a wider swath 3D image of an ice shelf. The 3D images can then be used to obtain a more complete estimate of the bottom melt rates of ice shelves