ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold

Tomographic SAR technique has attracted remarkable interest for its ability of three-dimensional resolving along the elevation direction via a stack of SAR images collected from different cross-track angles. The emerged compressed sensing (CS)-based algorithms have been introduced into TomoSAR considering its super-resolution ability with limited samples. However, the conventional CS-based methods suffer from several drawbacks, including weak noise resistance, high computational complexity, and complex parameter fine-tuning. Aiming at efficient TomoSAR imaging, this paper proposes a novel efficient sparse unfolding network based on the analytic learned iterative shrinkage thresholding algorithm (ALISTA) architecture with adaptive threshold, named Adaptive Threshold ALISTA-based Sparse Imaging Network (ATASI-Net). The weight matrix in each layer of ATASI-Net is pre-computed as the solution of an off-line optimization problem, leaving only two scalar parameters to be learned from data, which significantly simplifies the training stage. In addition, adaptive threshold is introduced for each azimuth-range pixel, enabling the threshold shrinkage to be not only layer-varied but also element-wise. Moreover, the final learned thresholds can be visualized and combined with the SAR image semantics for mutual feedback. Finally, extensive experiments on simulated and real data are carried out to demonstrate the effectiveness and efficiency of the proposed method

Emerging Approaches for THz Array Imaging: A Tutorial Review and Software Tool

Accelerated by the increasing attention drawn by 5G, 6G, and Internet of Things applications, communication and sensing technologies have rapidly evolved from millimeter-wave (mmWave) to terahertz (THz) in recent years. Enabled by significant advancements in electromagnetic (EM) hardware, mmWave and THz frequency regimes spanning 30 GHz to 300 GHz and 300 GHz to 3000 GHz, respectively, can be employed for a host of applications. The main feature of THz systems is high-bandwidth transmission, enabling ultra-high-resolution imaging and high-throughput communications; however, challenges in both the hardware and algorithmic arenas remain for the ubiquitous adoption of THz technology. Spectra comprising mmWave and THz frequencies are well-suited for synthetic aperture radar (SAR) imaging at sub-millimeter resolutions for a wide spectrum of tasks like material characterization and nondestructive testing (NDT). This article provides a tutorial review of systems and algorithms for THz SAR in the near-field with an emphasis on emerging algorithms that combine signal processing and machine learning techniques. As part of this study, an overview of classical and data-driven THz SAR algorithms is provided, focusing on object detection for security applications and SAR image super-resolution. We also discuss relevant issues, challenges, and future research directions for emerging algorithms and THz SAR, including standardization of system and algorithm benchmarking, adoption of state-of-the-art deep learning techniques, signal processing-optimized machine learning, and hybrid data-driven signal processing algorithms...Comment: Submitted to Proceedings of IEE

Infrared Image Super-Resolution: Systematic Review, and Future Trends

Image Super-Resolution (SR) is essential for a wide range of computer vision and image processing tasks. Investigating infrared (IR) image (or thermal images) super-resolution is a continuing concern within the development of deep learning. This survey aims to provide a comprehensive perspective of IR image super-resolution, including its applications, hardware imaging system dilemmas, and taxonomy of image processing methodologies. In addition, the datasets and evaluation metrics in IR image super-resolution tasks are also discussed. Furthermore, the deficiencies in current technologies and possible promising directions for the community to explore are highlighted. To cope with the rapid development in this field, we intend to regularly update the relevant excellent work at \url{https://github.com/yongsongH/Infrared_Image_SR_SurveyComment: Submitted to IEEE TNNL

Image Restoration

This book represents a sample of recent contributions of researchers all around the world in the field of image restoration. The book consists of 15 chapters organized in three main sections (Theory, Applications, Interdisciplinarity). Topics cover some different aspects of the theory of image restoration, but this book is also an occasion to highlight some new topics of research related to the emergence of some original imaging devices. From this arise some real challenging problems related to image reconstruction/restoration that open the way to some new fundamental scientific questions closely related with the world we interact with

Proceedings of the Augmented VIsual Display (AVID) Research Workshop

The papers, abstracts, and presentations were presented at a three day workshop focused on sensor modeling and simulation, and image enhancement, processing, and fusion. The technical sessions emphasized how sensor technology can be used to create visual imagery adequate for aircraft control and operations. Participants from industry, government, and academic laboratories contributed to panels on Sensor Systems, Sensor Modeling, Sensor Fusion, Image Processing (Computer and Human Vision), and Image Evaluation and Metrics

Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging Systems

Increasing attention is being paid to millimeter-wave (mmWave), 30 GHz to 300 GHz, and terahertz (THz), 300 GHz to 10 THz, sensing applications including security sensing, industrial packaging, medical imaging, and non-destructive testing. Traditional methods for perception and imaging are challenged by novel data-driven algorithms that offer improved resolution, localization, and detection rates. Over the past decade, deep learning technology has garnered substantial popularity, particularly in perception and computer vision applications. Whereas conventional signal processing techniques are more easily generalized to various applications, hybrid approaches where signal processing and learning-based algorithms are interleaved pose a promising compromise between performance and generalizability. Furthermore, such hybrid algorithms improve model training by leveraging the known characteristics of radio frequency (RF) waveforms, thus yielding more efficiently trained deep learning algorithms and offering higher performance than conventional methods. This dissertation introduces novel hybrid-learning algorithms for improved mmWave imaging systems applicable to a host of problems in perception and sensing. Various problem spaces are explored, including static and dynamic gesture classification; precise hand localization for human computer interaction; high-resolution near-field mmWave imaging using forward synthetic aperture radar (SAR); SAR under irregular scanning geometries; mmWave image super-resolution using deep neural network (DNN) and Vision Transformer (ViT) architectures; and data-level multiband radar fusion using a novel hybrid-learning architecture. Furthermore, we introduce several novel approaches for deep learning model training and dataset synthesis.Comment: PhD Dissertation Submitted to UTD ECE Departmen

Compressive Sensing for Microwave and Millimeter-Wave Array Imaging

PhDCompressive Sensing (CS) is a recently proposed signal processing technique that has already found many applications in microwave and millimeter-wave imaging. CS theory guarantees that sparse or compressible signals can be recovered from far fewer measure- ments than those were traditionally thought necessary. This property coincides with the goal of personnel surveillance imaging whose priority is to reduce the scanning time as much as possible. Therefore, this thesis investigates the implementation of CS techniques in personnel surveillance imaging systems with different array configurations. The first key contribution is the comparative study of CS methods in a switched array imaging system. Specific attention has been paid to situations where the array element spacing does not satisfy the Nyquist criterion due to physical limitations. CS methods are divided into the Fourier transform based CS (FT-CS) method that relies on conventional FT and the direct CS (D-CS) method that directly utilizes classic CS formulations. The performance of the two CS methods is compared with the conventional FT method in terms of resolution, computational complexity, robustness to noise and under-sampling. Particularly, the resolving power of the two CS methods is studied under various cir- cumstances. Both numerical and experimental results demonstrate the superiority of CS methods. The FT-CS and D-CS methods are complementary techniques that can be used together for optimized efficiency and image reconstruction. The second contribution is a novel 3-D compressive phased array imaging algorithm based on a more general forward model that takes antenna factors into consideration. Imaging results in both range and cross-range dimensions show better performance than the conventional FT method. Furthermore, suggestions on how to design the sensing con- figurations for better CS reconstruction results are provided based on coherence analysis. This work further considers the near-field imaging with a near-field focusing technique integrated into the CS framework. Simulation results show better robustness against noise and interfering targets from the background. The third contribution presents the effects of array configurations on the performance of the D-CS method. Compressive MIMO array imaging is first derived and demonstrated with a cross-shaped MIMO array. The switched array, MIMO array and phased array are then investigated together under the compressive imaging framework. All three methods have similar resolution due to the same effective aperture. As an alternative scheme for the switched array, the MIMO array is able to achieve comparable performance with far fewer antenna elements. While all three array configurations are capable of imaging with sub-Nyquist element spacing, the phased array is more sensitive to this element spacing factor. Nevertheless, the phased array configuration achieves the best robustness against noise at the cost of higher computational complexity. The final contribution is the design of a novel low-cost beam-steering imaging system using a flat Luneburg lens. The idea is to use a switched array at the focal plane of the Luneburg lens to control the beam-steering. By sequentially exciting each element, the lens forms directive beams to scan the region of interest. The adoption of CS for image reconstruction enables high resolution and also data under-sampling. Numerical simulations based on mechanically scanned data are conducted to verify the proposed imaging system.China Scholarship Council Engineering and Physical Sciences Research Council (EPSRC) funding (EP/I034548/1)

Hidrogeis multiestruturais obtidos através de estratégias biomiméticas para aplicações biomédicas

The extracellular matrix (ECM) of load-bearing soft tissues is characterized by a welldefined and complex architecture which is responsible for its high mechanical performance. Inspired by the native ECM of living tissues, we demonstrate the possibility to fabricate tough and cytocompatible hydrogels from a single polymeric precursor formulation and under physiological conditions. The designed systems were synthesized through an adapted Double-network (DN)-based methodology combining chemical and physical crosslinking mechanisms. Such multifunctional devices were able to withstand an impressive compressive stress in the same order of magnitude as the ones found in native load-bearing soft tissues, highlighting their potential for the repair of these tissues. Further improvements on the former DN-based hydrogel were made in order to achieve highly hydrated biomaterials with other advantageous properties for biomedical purposes, including self-healing and injectability. Inspired by the lotus-leaf liquid-repellence, our group proposed a simple, straightforward and cost-effective tool to produce spherical polymeric particles above artificial superantiwetting surfaces. In this thesis, this biomimetic strategy was used to fabricate a large variety of natural-based hydrogel spherical systems with distinct macroscopic structures. First, reversible superamphiphobic (SA) surfaces were fabricated by covering a substrate with specifically designed microcapsules entrapping magnetic particles. The main advantage of using magnetic responsive particles is the ability to control their arrangement and fixation over the substrate by applying an external magnetic field. The produced non-permanent SA surfaces were successfully employed to fabricate water/oil repellent surfaces, liquid marbles and microfluidic channels and, also used as templates for the fabrication of spherical particles. Second, SA surfaces were successfully employed as supports to produce spherical polymeric microparticles with potential as cell and drug carriers. The proposed strategy consists in spraying a hydrogel precursor solution over a SA surface followed by a crosslinking mechanism. Next, hierarchical systems were also created via the assembly of polymeric spherical particles induced by these artificial SA substrates under physiological conditions. Finally, SA surfaces were successfully employed to fabricate ready-to-use and stable liquefied capsules enclosing different objects, such as cells and drugs. All these bioinspired strategies are poised to usher the development of the next generation of engineered hydrogel devices for biomedicine and tissue engineering.A matriz extracelular dos tecidos moles é caraterizada por uma estrutura definida e complexa, sendo responsável pelas suas extraordinárias propriedades mecânicas. Usando a matriz extracelular como inspiração, foi demonstrada a possibilidade de produzir hidrogéis robustos e citocompatíveis sob condições fisiológicas. Os materiais obtidos foram sintetizados através de uma adaptação da metodologia Double-network (DN), combinando mecanismos de reticulação físicos e químicos. Estes sistemas multifuncionais são capazes de suportar tensões mecânicas na mesma ordem de grandeza das encontradas nos tecidos estruturais do corpo, o que reforça o potencial destes biomateriais hidratados para reparar estes mesmos tecidos. Estes géis DN foram melhorados de modo a obter materiais com outras características importantes para aplicações biomédicas, nomeadamente a capacidade de se autorrepararem e serem administrados através de estratégias minimamente invasivas, como por injeção. Adicionalmente, o nosso grupo desenvolveu uma nova metodologia, inspirada pela capacidade de a folha de lótus repelir líquidos, para produzir partículas poliméricas com uma forma esférica. Esta técnica consiste em dispensar uma solução polimérica sobre uma superfície com extrema repelência a líquidos e, de seguida, um processo de reticulação é aplicado à gota polimérica de modo a reter a sua forma esférica. Nesta tese, esta estratégia biomimética foi usada para fabricar diversos sistemas esféricos com variadas estruturas macroscópicas. Primeiro, superfícies reversíveis e superanfifóbicas (SA) foram criadas através da deposição de microcápsulas contendo partículas magnéticas no seu interior sobre um suporte sólido. A principal vantagem de usar partículas sensíveis a campos magnéticos é a possibilidade de controlar a sua posição e fixação a um suporte usando um íman. Estas superfícies SA foram usadas como suportes para produzir partículas esféricas e canais de microfluídica. De seguida, partículas poliméricas com tamanhos na escala micrométrica foram obtidos, pela primeira vez, usando superfícies SA. A estratégia desenvolvida consiste em dispensar, sob uma superfície SA, uma solução polimérica usando um pulverizador e, de seguida, um mecanismo de reticulação é aplicado de modo a obter hidrogéis esféricos. Adicionalmente, foram também criadas partículas multicompartimentalizadas com uma estrutura hierárquica incorporando as micropartículas produzidas anteriormente. Finalmente, as superfícies SA foram também usadas para obter cápsulas esféricas compostas por uma camada externa polimérica e um núcleo no estado líquido. Diferentes objetos como células e moléculas bioativas podem ser encapsulados no interior das partículas anteriores, reforçando o seu potencial biomédico. É antecipado que todas estas estratégias biomiméticas sejam importantes para o desenvolvimento da nova geração de hidrogéis com potencial em biomedicina e engenharia de tecidos.Programa Doutoral em Químic

Direction of Arrival Estimation in Low-Cost Frequency Scanning Array Antenna Systems

RÉSUMÉ Cette thèse propose des méthodes d'estimation de la direction d'arrivée (DOA) et d'amélioration de la résolution angulaire applicables aux antennes à balayage de fréquence (Frequency Scanning Antenna ou FSA) et présente un développement analytique et des confirmations expérimentales des méthodes proposées. Les FSA sont un sous-ensemble d'antennes à balayage électronique dont l'angle du faisceau principal change en faisant varier la fréquence des signaux. L'utilisation des FSA est un compromis entre des antennes à balayage de phase (phased arrays antennas) plus coûteuses et plus complexes, et des antennes à balayage mécanique plus lentes et non agiles. Bien que l'agilité et le faible coût des FSA les rendent un choix plausible dans certaines applications, les FSA à faible coût peuvent ne pas être conformes aux exigences souhaitées pour l'application cible telles que les exigences de résolution angulaire. Ainsi, cette recherche tente d'abord de caractériser les capacités de résolution angulaire de certains systèmes d'antennes FSA sélectionnés. Elle poursuit en explorant des modifications ou extensions aux algorithmes de super-résolution capables d'améliorer la résolution angulaire de l'antenne et de les adapter pour être appliqués aux FSA. Deux méthodes d'estimation de la résolution angulaire, l'estimation du maximum de vraisemblance (Maximum Likelihood ou ML) et la formation du faisceau de variance minimale de Capon (Minimum Variance Beamforming ou MVB) sont étudiées dans cette recherche. Les deux méthodes sont modifiées pour être applicables aux FSA. De plus, les méthodes d'étalonnage et de pré-traitement requises pour chaque méthode sont également introduites. Les résultats de simulation ont montré qu'en sélectionnant des paramètres corrects, il est possible d'améliorer la résolution angulaire au-delà de la limitation de la largeur de faisceau des FSA en utilisant les deux méthodes. Les critères pour lesquels chaque méthode fonctionne le mieux sont discutés et l'analyse pour justifier les conditions présentées est donnée.----------ABSTRACT This research investigates direction of arrival (DOA) estimation and angular resolution enhancement methods applicable to frequency scanning antennas (FSA) and provides analytical development and experimental validation for the proposed methods. FSAs are a subset of electronically scanning antennas, which scan the angle of their main beam by varying the frequency of the signals. Using FSA is a trade-off between more expensive and complex phase array antennas and slower and non-agile mechanical scanning antennas. Although agility and low-cost of FSAs make them a plausible choice in some application, low-cost FSAs may not comply with the desired requirements for the target application such as angular resolution requirements. Thus, this research attempts to first characterize the angular resolution capabilities of some selected FSA antenna systems, and then modify or extend super-resolution algorithms capable of enhancing the angular resolution of the antenna and adapt them to be applied to FSAs. Two angular resolution estimation methods, maximum likelihood estimation (ML) and Capon minimum variance beamforming (MVB), are studied in this research. Both methods are modified to be applicable to FSAs. In addition, the calibration and pre-processing methods required for each method are also introduced. Simulation results show that by selecting correct parameters, it is possible to enhance angular resolution beyond the beamwidth limitation of FSAs using both methods. The criteria for which each method performs the best are discussed and an analysis supporting the presented conditions are given. The proposed methods are also validated using the measured antenna radiation pattern of an 8-element FSA which is built based on a composite right/left-handed (CRLH) waveguide. In addition, the experimental results using a beam scanning parabolic reflector antenna using a frequency multiplexed antenna feed is given. The design limitations of this antenna reduces the performance of angular resolution enhancement methods. Therefore, a hybrid scanning system combining mechanical and frequency scanning using the beam scanning reflector antenna is also proposed