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

Bayesian super-resolution with application to radar target recognition

This thesis is concerned with methods to facilitate automatic target recognition using images generated from a group of associated radar systems. Target recognition algorithms require access to a database of previously recorded or synthesized radar images for the targets of interest, or a database of features based on those images. However, the resolution of a new image acquired under non-ideal conditions may not be as good as that of the images used to generate the database. Therefore it is proposed to use super-resolution techniques to match the resolution of new images with the resolution of database images. A comprehensive review of the literature is given for super-resolution when used either on its own, or in conjunction with target recognition. A new superresolution algorithm is developed that is based on numerical Markov chain Monte Carlo Bayesian statistics. This algorithm allows uncertainty in the superresolved image to be taken into account in the target recognition process. It is shown that the Bayesian approach improves the probability of correct target classification over standard super-resolution techniques. The new super-resolution algorithm is demonstrated using a simple synthetically generated data set and is compared to other similar algorithms. A variety of effects that degrade super-resolution performance, such as defocus, are analyzed and techniques to compensate for these are presented. Performance of the super-resolution algorithm is then tested as part of a Bayesian target recognition framework using measured radar data

Fourier optics approaches to enhanced depth-of-field applications in millimetre-wave imaging and microscopy

In the first part of this thesis millimetre-wave interferometric imagers are considered for short-range applications such as concealed weapons detection. Compared to real aperture systems, synthetic aperture imagers at these wavelengths can provide improvements in terms of size, cost, depth-of-field (DoF) and imaging flexibility via digitalrefocusing. Mechanical scanning between the scene and the array is investigated to reduce the number of antennas and correlators which drive the cost of such imagers. The tradeoffs associated with this hardware reduction are assessed before to jointly optimise the array configuration and scanning motion. To that end, a novel metric is proposed to quantify the uniformity of the Fourier domain coverage of the array and is maximised with a genetic algorithm. The resulting array demonstrates clear improvements in imaging performances compared to a conventional power-law Y-shaped array. The DoF of antenna arrays, analysed via the Strehl ratio, is shown to be limited even for infinitely small antennas, with the exception of circular arrays. In the second part of this thesis increased DoF in optical systems with Wavefront Coding (WC) is studied. Images obtained with WC are shown to exhibit artifacts that limit the benefits of this technique. An image restoration procedure employing a metric of defocus is proposed to remove these artifacts and therefore extend the DoF beyond the limit of conventional WC systems. A transmission optical microscope was designed and implemented to operate with WC. After suppression of partial coherence effects, the proposed image restoration method was successfully applied and extended DoF images are presented

Three-dimensional reconstruction methods for micro-rotation fluorescence microscopy

Micro-rotation fluorescence microscopy is a novel, optical imaging technique developed with a cell rotation system. The imaging system enables individual living cells to be rotated in suspension under microscopic dimensions, and allows us to acquire a series of images of the cells, simultaneously during the rotation. A challenging task in micro-rotation imaging is how to determine three-dimensional (3D) cell structure from the image series. This thesis thus presents four alternative methods for reconstructing 3D objects from a series of micro-rotation images. The three former methods, the expectation maximisation (EM), the generalised Skilling-Bryan and the marginalisation methods, are iterative algorithms built on the Bayesian inversion theory, which is used to quantify uncertainties in data and model parameters, and also to utilise prior information about the unknown structure. The fourth method, dual filtered backprojection (DFBP), is a fast, non-iterative algorithm derived from the Fourier slice theorem in the classical computed tomography. Each method has its own features: the EM method serves as a basic tool for general usability; the Skilling-Bryan method is more flexible for modelling of noise and prior; the marginalisation method serves as a statistical treatment of the reconstruction that suffers from inaccurate image alignment; and the DFBP method beats the other methods by computational speed but restricts itself with a certain imaging condition. In general, selection of the reconstruction methods depends on imaging and data conditions, such as conventional widefield or confocal microscopy, the stability of cell rotation, and the quality of image alignment. In conclusion, all the proposed reconstruction methods clearly increase capability to visualise 3D object structures, as shown by both simulations and experiments with real micro-rotation data. Two obvious messages from the results are that first, the quality of the reconstructed object highly depends on the accuracy of image alignment, and second, micro-rotation reconstructions with the current imaging system always contain poor resolution in the tangential direction of the rotation. Future interesting research is thus to combine the micro-rotation protocol with extended depth-of-focus microscopy that could strengthen the tangential resolution

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

Optimization of the holographic process for imaging and lithography

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 272-297).Since their invention in 1948 by Dennis Gabor, holograms have demonstrated to be important components of a variety of optical systems and their implementation in new fields and methods is expected to continue growing. Their ability to encode 3D optical fields on a 2D plane opened the possibility of novel applications for imaging and lithography. In the traditional form, holograms are produced by the interference of a reference and object waves recording the phase and amplitude of the complex field. The holographic process has been extended to include different recording materials and methods. The increasing demand for holographic-based systems is followed by a need for efficient optimization tools designed for maximizing the performance of the optical system. In this thesis, a variety of multi-domain optimization tools designed to improve the performance of holographic optical systems are proposed. These tools are designed to be robust, computationally efficient and sufficiently general to be applied when designing various holographic systems. All the major forms of holographic elements are studied: computer generated holograms, thin and thick conventional holograms, numerically simulated holograms and digital holograms. Novel holographic optical systems for imaging and lithography are proposed. In the case of lithography, a high-resolution system based on Fresnel domain computer generated holograms (CGHs) is presented. The holograms are numerically designed using a reduced complexity hybrid optimization algorithm (HOA) based on genetic algorithms (GAs) and the modified error reduction (MER) method. The algorithm is efficiently implemented on a graphic processing unit. Simulations as well as experimental results for CGHs fabricated using electron-beam lithography are presented. A method for extending the system's depth of focus is proposed. The HOA is extended for the design and optimization of multispectral CGHs applied for high efficiency solar concentration and spectral splitting. A second lithographic system based on optically recorded total internal reflection (TIR) holograms is studied. A comparative analysis between scalar and (cont.) vector diffraction theories for the modeling and simulation of the system is performed.A complete numerical model of the system is conducted including the photoresist response and first order models for shrinkage of the holographic emulsion. A novel block-stitching algorithm is introduced for the calculation of large diffraction patterns that allows overcoming current computational limitations of memory and processing time. The numerical model is implemented for optimizing the system's performance as well as redesigning the mask to account for potential fabrication errors. The simulation results are compared to experimentally measured data. In the case of imaging, a segmented aperture thin imager based on holographically corrected gradient index lenses (GRIN) is proposed. The compound system is constrained to a maximum thickness of 5mm and utilizes an optically recorded hologram for correcting high-order optical aberrations of the GRIN lens array. The imager is analyzed using system and information theories. A multi-domain optimization approach is implemented based on GAs for maximizing the system's channel capacity and hence improving the information extraction or encoding process. A decoding or reconstruction strategy is implemented using the superresolution algorithm. Experimental results for the optimization of the hologram's recording process and the tomographic measurement of the system's space-variant point spread function are presented. A second imaging system for the measurement of complex fluid flows by tracking micron sized particles using digital holography is studied. A stochastic theoretical model based on a stability metric similar to the channel capacity for a Gaussian channel is presented and used to optimize the system. The theoretical model is first derived for the extreme case of point source particles using Rayleigh scattering and scalar diffraction theory formulations. The model is then extended to account for particles of variable sizes using Mie theory for the scattering of homogeneous dielectric spherical particles. The influence and statistics of the particle density dependent cross-talk noise are studied. Simulation and experimental results for finding the optimum particle density based on the stability metric are presented. For all the studied systems, a sensitivity analysis is performed to predict and assist in the correction of potential fabrication or calibration errors.by José Antonio Domínguez-Caballero.Ph.D

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Informational limits in optical polarimetry and vectorial imaging

Light has provided the means to learn and gather information about the physical world throughout history. In a world where science moves to smaller scales and more specialised problems however, the boundaries of current technology are continually challenged, motivating the search for more sophisticated systems providing greater information content, sensitivity and increased dimensionality. Utilising the vectorial nature of light presents a promising avenue by which to meet these growing requirements. Polarisation can, for example, be used to transmit information, or alternatively, changes in polarisation induced by an object allow study of previously neglected material properties, such as birefringence and diattenuation. Central to this thesis is thus the characterisation and exploitation of the opportunities afforded by the electromagnetic (i.e. vectorial) nature of light. To this end the work follows three running themes: quantification of polarisation information; formulation of simple propagation tools for electromagnetic waves; and development of specific polarisation based optical systems. Characterising the informational limits inherent to polarisation based systems reduces to considering the uncertainty present in any observations. Uncertainty can, for example, arise from stochastic variation in the polarisation state being measured, or from random noise perturbations upon detection. Both factors are considered and quantified here. Development of vectorial optical systems does, however, pose significant difficulties in modelling, due to mathematical complexity and computational requirements. A number of new tools are hence developed, as prove applicable to a wide variety of applications. Examples are naturally given. To illustrate the potential of polarisation based systems, specific current topics are discussed; namely the growing demand for data storage, and single molecule studies. It will be shown that polarisation, can not only be used to multiplex information in data pits on optical media, but also to allow full 3D study of single molecules. Factors pertinent to such studies are studied in detail