Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

undefine

Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

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

Recent Techniques for Regularization in Partial Differential Equations and Imaging

abstract: Inverse problems model real world phenomena from data, where the data are often noisy and models contain errors. This leads to instabilities, multiple solution vectors and thus ill-posedness. To solve ill-posed inverse problems, regularization is typically used as a penalty function to induce stability and allow for the incorporation of a priori information about the desired solution. In this thesis, high order regularization techniques are developed for image and function reconstruction from noisy or misleading data. Specifically the incorporation of the Polynomial Annihilation operator allows for the accurate exploitation of the sparse representation of each function in the edge domain. This dissertation tackles three main problems through the development of novel reconstruction techniques: (i) reconstructing one and two dimensional functions from multiple measurement vectors using variance based joint sparsity when a subset of the measurements contain false and/or misleading information, (ii) approximating discontinuous solutions to hyperbolic partial differential equations by enhancing typical solvers with l1 regularization, and (iii) reducing model assumptions in synthetic aperture radar image formation, specifically for the purpose of speckle reduction and phase error correction. While the common thread tying these problems together is the use of high order regularization, the defining characteristics of each of these problems create unique challenges. Fast and robust numerical algorithms are also developed so that these problems can be solved efficiently without requiring fine tuning of parameters. Indeed, the numerical experiments presented in this dissertation strongly suggest that the new methodology provides more accurate and robust solutions to a variety of ill-posed inverse problems.Dissertation/ThesisDoctoral Dissertation Mathematics 201

COMPRESSIVE IMAGING AND DUAL MOIRE´ LASER INTERFEROMETER AS METROLOGY TOOLS

Metrology is the science of measurement and deals with measuring different physical aspects of objects. In this research the focus has been on two basic problems that metrologists encounter. The first problem is the trade-off between the range of measurement and the corresponding resolution; measurement of physical parameters of a large object or scene accompanies by losing detailed information about small regions of the object. Indeed, instruments and techniques that perform coarse measurements are different from those that make fine measurements. This problem persists in the field of surface metrology, which deals with accurate measurement and detailed analysis of surfaces. For example, laser interferometry is used for fine measurement (in nanometer scale) while to measure the form of in object, which lies in the field of coarse measurement, a different technique like moire technique is used. We introduced a new technique to combine measurement from instruments with better resolution and smaller measurement range with those with coarser resolution and larger measurement range. We first measure the form of the object with coarse measurement techniques and then make some fine measurement for features in regions of interest. The second problem is the measurement conditions that lead to difficulties in measurement. These conditions include low light condition, large range of intensity variation, hyperspectral measurement, etc. Under low light condition there is not enough light for detector to detect light from object, which results in poor measurements. Large range of intensity variation results in a measurement with some saturated regions on the camera as well as some dark regions. We use compressive sampling based imaging systems to address these problems. Single pixel compressive imaging uses a single detector instead of array of detectors and reconstructs a complete image after several measurements. In this research we examined compressive imaging for different applications including low light imaging, high dynamic range imaging and hyperspectral imaging

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

Adaptive OFDM Radar for Target Detection and Tracking

We develop algorithms to detect and track targets by employing a wideband orthogonal frequency division multiplexing: OFDM) radar signal. The frequency diversity of the OFDM signal improves the sensing performance since the scattering centers of a target resonate variably at different frequencies. In addition, being a wideband signal, OFDM improves the range resolution and provides spectral efficiency. We first design the spectrum of the OFDM signal to improve the radar\u27s wideband ambiguity function. Our designed waveform enhances the range resolution and motivates us to use adaptive OFDM waveform in specific problems, such as the detection and tracking of targets. We develop methods for detecting a moving target in the presence of multipath, which exist, for example, in urban environments. We exploit the multipath reflections by utilizing different Doppler shifts. We analytically evaluate the asymptotic performance of the detector and adaptively design the OFDM waveform, by maximizing the noncentrality-parameter expression, to further improve the detection performance. Next, we transform the detection problem into the task of a sparse-signal estimation by making use of the sparsity of multiple paths. We propose an efficient sparse-recovery algorithm by employing a collection of multiple small Dantzig selectors, and analytically compute the reconstruction performance in terms of the $ell_1$-constrained minimal singular value. We solve a constrained multi-objective optimization algorithm to design the OFDM waveform and infer that the resultant signal-energy distribution is in proportion to the distribution of the target energy across different subcarriers. Then, we develop tracking methods for both a single and multiple targets. We propose an tracking method for a low-grazing angle target by realistically modeling different physical and statistical effects, such as the meteorological conditions in the troposphere, curved surface of the earth, and roughness of the sea-surface. To further enhance the tracking performance, we integrate a maximum mutual information based waveform design technique into the tracker. To track multiple targets, we exploit the inherent sparsity on the delay-Doppler plane to develop an computationally efficient procedure. For computational efficiency, we use more prior information to dynamically partition a small portion of the delay-Doppler plane. We utilize the block-sparsity property to propose a block version of the CoSaMP algorithm in the tracking filter

GROUND DEFORMATION ANALYSIS IN APENNINE AREAS, SEISMICALLY ACTIVE OR ASEISMIC, USING DATA FROM SAR INTERFEROMETRY AND INTEGRATION OF GEOMORPHOLOGICAL AND STRUCTURAL DATA

The core of the study herein has been the analysis of PS-InSAR datasets aimed at providing new constraints to the active tectonics framework, and seismotectonics, of several regions of the Apennines. The analysed Permanent Scatterers datasets result from processing of large amounts of temporally continuous series of radar images acquired with the ERS (1992-2000), ENVISAT (2003-2010) and COSMO SKYMED (2011-2014) satellite missions. Such datasets, which are available in the cartographic website (Geoportale Nazionale) of the Italian Ministry of Environment (MATTM) have been collected through time by the MATTM in the frame of the "Extraordinary Remote Sensing Plan" (Piano Straordinario di Telerilevamento Ambientale, PST-A, law n. 179/2002 - article 27), with the aim of supporting local administrations in the field of environmental policies. The database was realized through three phases: the first one (2008-2009), which involved the interferometric processing of SAR images acquired throughout the country by the ERS1/ERS2 and ENVISAT satellites in both ascending and descending orbits, from 1992 to 2008; the second one (2010-2011) integrated the existing database with the processing of the SAR images acquired by the ENVISAT satellite from 2008 to 2010; the third phase (2013-2015) provided an upgrading and updating of the previously developed database on critical areas, based on StripMap H image acquired with a 16-day recurrence, either in ascending or descending orbit, using the Italian national satellite system, the COSMO SKYMED. With this study, a massive use of Permanent Scatterer datasets is applied for the first time at assessment of ground deformation of large (hundreds of km2 wide) regions of Italy over the last decades, in order to unravelling their current tectonic behaviour. To date in the field of tectonics – in particular, of earthquake geology - the SAR images have been used essentially through the DinSAR technique (comparison between two images, acquired pre- and post-event) in order to constrain the co- and post-seismic deformation (Massonet et al., 1993; Peltzer et al., 1996, 1998; Stramondo et al., 1999; Atzori et al., 2009; Copley and Reynolds, 2014), while the approach that has been used in the case studies that are the object of the research herein is based on analyses of data that (with the exception of the Lunigiana case study) cover an about 20-year long time window. The opportunity of analysing so long, continuous SAR records has allowed detection of both coseismic displacement of moderate earthquakes (i.e., the M 6.3 2009 L’Aquila earthquake, and the M 5 2013 Lunigiana earthquake), and subdued ground displacements - and acceleration – on time scale ranging from yearly to decades. The specific approach used in this study rests on a combination of various techniques of analysis and processing of the PS datasets. In general, as the analyses that have been carried out aimed at identifying motion values with wide areal extent, a statistical filtering has been applied to PSs velocity values in order to discard from the initial, “native”, dataset fast-moving PSs that may be associated with the occurrence of local-scale phenomena (e.g., landslides, sediment compaction, water extraction, etc.). Furthermore, an in depth inspection of time series of PSs from all of the investigated areas has been carried out with the aim of identifying changing (LoS-oriented) motion trends over the analysed time windows. A distinctive feature of this study was the estimation of vertical ground displacements. In fact, while most studies on ground deformation are based on analysis of SAR data recorded along either ascending or descending satellite orbits (thus based on LoS-oriented motions), a specific focus of this study was to obtain - starting from LoS-oriented PS velocity values - displacement values in the vertical plane oriented west-east. In order to evaluate vertical displacements, a geometrical relationship was applied to ascending - descending PSs pairs. As PS from ascending and descending tracks are neither spatially coincident nor synchronous, each image pair was obtained by selecting ascending-descending radar images with a time separation within one month. In the L’Aquila region case study, the combination of data recorded along both the ascending and descending satellite orbits has been crucial to the identification of pre-seismic ground motions, undetected in previous works that – similarly – had addressed assessment of possible pre-seismic satellite-recorded signals. In the various case studies, different kinds of GIS-aided geostatistical analyses were used to extract and synthesise information on ground deformation through the construction of both raster maps of displacement values for the ascending and descending LoS, respectively, and maps of the vertical (z, up - down) component of the “real” displacement vector. In the Campania plain case study, the PS-InSAR data analysis and processing have been integrated by detail scale geomorphological-stratigraphical analysis. Results of analyses of the two independent data sets are consistent, and point to tectonically-controlled ground displacements in a large part of the northern part of the study area (Volturno plain) during the 1992-2010 analysed time span. In particular, the integrated data sets show that the boundaries of the area affected by current subsidence follow fault scarps formed in the 39 ka old Campania Ignimbrite, while the horst blocks of such faults are substantially stable (or slightly uplifting) during the analysed time window. Furthermore, mean rates of current subsidence and long-term (Late Pleistocene to present) mean subsidence rates are comparable, pointing to current vertical displacement assessed through the PS-InSAR data analysis as the expression of the recent tectonics of the analysed sectors of the Campania plain. The Campania plain substantially lacks strong historical seismicity. Such evidence suggests that the detected surface displacements result at least in part from aseismic fault activity. The Monte Marzano case study has allowed assessment of subdued deformation along both the major structures that were activated with the Irpinia 1980 earthquake, i.e. the NE-dipping Monte Marzano fault and the SW-dipping Conza fault, respectively. Ground deformation associated with such structures appears decreasing from the time window covered by the ERS satellites (1992-2000) to that covered by the ENVISAT (2003-2010). These data suggest that post-seismic slip of the M 6.9 has continued until 20 years after the main shock to become very weak in the following ten years. Furthermore, the PS-InSAR data analysis has shown that wide areas located between the Monte Marzano and Conza faults (i.e., in the one that is recognised as the graben structure bounded by those structures) show uplift in the range of 0-2 mm/yr, more evident in the period surveyed by the ERS satellites (1992-2000) and less evident in the 2003-2010 time span (ENVISAT). Such uplift might be related to the occurrence, at depth, of a fluid reservoir that has been independently identified by seismic tomography (Amoroso et al., 2014). In depth analysis of pre-seismic periods have been carried out in three study areas, i.e. those of the 1997 Colfiorito earthquake, of the 2009 L’Aquila earthquake and of the 2013 Lunigiana earthquake. The Colfiorito case study has not provided any significant information on possible pre-seismic ground deformation, most probably due to the PS spatial distribution in that region too much discontinuous to allow identification of both net signals from inspection of the rare and sparse PS time series, and statistically meaningful surface displacement patterns. Both in the L’Aquila and Lunigiana case studies, ground deformation signals in the pre-seismic period have been detected from inspection of PS time series. Pre-seismic ground deformation signals detected in the Lunigiana area (which was affected by a strike-slip faulting earthquake; Eva et al., 2014, Pezzo et al., 2014, Stramondo et al., 2014) are questionable, as they are quite complex and difficult to be interpreted and framed within the local tectonic scenario. Conversely, very clear and net pre-seismic signals have been identified in the region hit by the L’Aquila normal faulting earthquake. There, in the time span predating of some four years the 6th April 2009 main shock, ground deformation with distinct spatial patterns, and orientations, have been detected. In particular, the PS-InSAR analysis has shown that the hanging wall block of the Paganica fault (the surface expression of the structure activated with the main shock; e.g., Galli et al., 2010) has been subject to slow uplift and eastward horizontal motion from 2005 to September/October 2008, and then (October 2008-March 2009) subject to subsidence and westward oriented horizontal motion. Following coseismic collapse, in the early post-seismic period (April-May 2009), subsidence extended eastwards beyond the Paganica fault trace. The region affected by opposite pre-seismic motions covers the area in which the 6th April main shock and most of both foreshocks and aftershocks (Valoroso et al., 2013) were recorded, while the inversion of the pre-seismic displacements is coeval with onset of the foreshocks (October 2008; Di Luccio et al., 2010). In addition, such a region includes both topographic highs and lows. All of such features point to a correlation of the detected motions with the seismic phenomena, and suggest a deep-seated causative mechanism, such as volume changes in response to vertical/lateral fluids migration and fracturing processes at depth, with all phenomena having been documented in connection with the 2009 earthquake in the study region (e.g., Di Luccio et al., 2010; Lucente et al., 2010; Moro et al., 2017). Pre-seismic ground deformation that has been detected in the L’Aquila region could represent a precursor signal of the 2009, M 6.3 earthquake. Such a hypothesis should be tested, in the future, through the continuous monitoring through SAR satellites, but also high-resolution geodetic techniques, of seismically active regions worldwide aimed at detecting the possible occurrence of pre-seismic signals. However, the results of this study point to the long-term (yearly scale) PS-InSAR technique as a tool crucial to the detection of ground deformation in areas struck by recent earthquakes, and to monitoring active – possibly aseismic - structures. Such knowledge may strongly support strategies addressed at territorial planning and mitigation of seismic hazard, and represent an important sustenance for actions ruled by Civil Protection. On the other hand, the results of this study highlight the importance of the existing PS database, and the importance of continuing implementing such an instrument in the future

Development and Improvement of Airborne Remote Sensing Radar Platforms

With the recent record ice melt in the Arctic as well as the dramatic changes occurring in the Antarctic, the need and urgency to characterize ice sheets in these regions has become a research thrust of both the NSF and NASA. Airborne remote sensing is the most effective way to collect the necessary data on a large scale with fine resolution. Current models for determining the relationship between the world's great ice sheets and global sea-level are limited by the availability of data on bed topography, glacier volume, internal layers, and basal conditions. This need could be satisfied by equipping long range aircraft with an appropriately sensitive suite of sensors. The goal of this work is to enable two new airborne radar installations for use in cryospheric surveying, and improve these systems as well as future systems by addressing aircraft integration effects on antenna-array performance. An aerodynamic fairing is developed to enable a NASA DC-8 to support a 5-element array for CReSIS's MCoRDS radar, and several structures are also developed to enable a NASA P-3 to support a 15-element MCoRDS array, as well as three other radar antenna-arrays used for cryospheric surveying. Together, these aircraft have flown almost 200 missions and collected 550 TB of unique science data. In addition, a compensation method is developed to improve beamforming and clutter suppression on wing-mounted arrays by mitigating phase center errors due to wing-flexure. This compensation method is applied to the MVDR beamforming algorithm to improve clutter suppression by using element displacement information to apply appropriate phase shifts. The compensation demonstrated an average SINR increase of 5-10 dB. The hardware contributions of this work have substantially contributed to the state-of-the-art for polar remotes sensing, as evidenced by new data sets made available to the science community and widespread use and citation of the data. The investigations of aircraft integration effects on antenna-arrays will improve future data sets by characterizing the performance degradation. The wing-flexure compensation will greatly improve beam formation and clutter suppression. Increased clutter suppression in airborne radars is crucial to improving next generation ice sheet models and sea-level rise predictions

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