Synthesis of multi-layer frequency selective surfaces of quasi-optical systems

This thesis investigate design techniques for multilayer Frequency Selective Surfaces (FSS) and its applications in quasi-optical (QO) systems. Design challenges that involve higher order filter and practical implementation of multilayer FSS at higher frequencies are reviewed. Multilayer FSS structures are commonly realized by cascading two or more FSS panel to achieve higher order responses, which usually rely on dielectric substrates to support the FSS arrays. It is noted that existing design approaches involved elaborate manufacturing processes as well as the requirement of custom dielectric thickness for the implementation of multilayer FSS. These design issues poses practical problems in the realization of multilayer FSS of higher order and its demonstration at higher frequencies. Furthermore, realization of higher order multilayer FSS with custom dielectric thicknesses are not feasible with low cost Printed Circuit Board (PCB) technology. As a result of this investigation, a novel design and synthesis technique is developed to address the aforementioned design issues. Equivalent circuit modelling and full wave electromagnetic simulation are employed for this purpose. The developed design technique enable practical realization of QO filter to have all transmission lines of predefined fix length. As a result, the proposed technique is able to resolve the limited availability of custom dielectric thicknesses, thus enable demonstration of multilayer FSS of higher order at higher frequencies. Particularly, the proposed design methodology allow rectification by design to adapt to any small variations in the dielectric thicknesses. Subsequently, based on this technique, a novel QO reflector design is developed to demonstrate proof of concept for time delay multiplexing that are employed in a radar system. The implementation of time delay between two polarization multiplexed beams initially requires true time delay structures that are difficult to integrate due to their electrically large structure. In order to address this problem, the designed QO reflector is able to perform same functionalities, i.e. a significant group delay difference for the two orthogonal linear polarization. Specifically, the designed QO reflector has the capability to de-multiplex an incoming wave into two linear polarized waves, whereby one of the reflected wave is time delayed while the other wave is unaffected. A synthesis method for QO reflector design with time delay multiplexing has been presented. Based on the design procedures reported in this thesis, prototypes for both QO filter and QO reflector of fourth order has been developed to operate at 15 GHz with 5% and 3.5% bandwidth respectively. The performances of the developed prototypes are verified with free-space measurement setup. The measured insertion loss of the QO filter is observed to be in the range of 0.5 dB – 2.83 dB, while the measured return loss of the QO reflector is the range of 1.5 dB – 2.3 dB. In order to demonstrate the effect of the group delay from the QO reflector, frequency domain analysis is performed by post-processing the measured data to obtain the required time domain signals. Overall the experimental measurement results corroborate well with both full-wave and circuit simulation

Free-induction-decay magnetometer with enhanced optical pumping

Spin preparation prior to a free-induction-decay (FID) measurement can be adversely affected by transverse bias fields, particularly in the geophysical field range. A strategy that enhances the spin polarization accumulated before readout is demonstrated, by synchronizing optical pumping with a magnetic field pulse that supersedes any transverse fields by over two order of magnitude. The pulsed magnetic field is generated along the optical pumping axis using a compact electromagnetic coil pair encompassing a micro-electromechanical systems (MEMS) vapor cell. The coils also resistively heat the cesium (Cs) vapor to the optimal atomic density without spurious magnetic field contributions as they are rapidly demagnetized to approximately zero field during spin readout. The demagnetization process is analyzed electronically, and directly with a FID measurement, to confirm that the residual magnetic field is minimal during detection. The sensitivity performance of this technique is compared to existing optical pumping modalities across a wide magnetic field range. A noise floor sensitivity of $238\,\mathrm{fT/\surd{Hz}}$ was achieved in a field of approximately $\mathrm{50\,\mu{T}}$, in close agreement with the Cram\'{e}r-Rao lower bound (CRLB) predicted noise density of $258\,\mathrm{fT/\surd{Hz}}$.Comment: 10 pages, 7 figure

Design and implementation of a microstrip filter biosensor for healthcare applications

PhD ThesisThe aim of this research was to develop high-frequency biosensors by a combination of traditional microstrip filters and microfluidics. Lowpass and bandpass microstrip filters were designed for operational frequencies less than 3 GHz. Analytical modelling was used to initially determine microstrip filter geometry and then 3D electromagnetic simulation software utilised to examine their performance. Once the design was optimised, devices were fabricated using traditional PCB manufacturing approaches and clean room evaporation techniques. The fabricated filters were compared with the simulation results. The characteristic filter features at 0.66 GHz, 0.80 GHz, and 1.60 GHz demonstrated good agreement to within 90% of the simulated models. Microfluidic reservoirs were then attached to the microstrip filters prior to biological testing. The targeted biomolecules for detection were prostate specific antigen (PSA). A vector network analyser was used to measure the S-parameters of the filters at each stage of functionalisation and immobilisation. Biosensor performance was assessed by measurement of the resonant amplitude and frequency shifts at the characteristic operational frequencies as a function of concentration of the immobilised PSA. The efficacy test of the produced biosensors demonstrated label-free detection down to a minimum analyte concentration of 6.125 ng/ml, this corresponding to an amplitude change of 9 dB and a frequency shift of 10 MHz in the characteristic feature of the S11 signal. This work has demonstrated the applicability of both lowpass and bandpass microstrip filters, with an operational frequency range less than 3 GHz and with suitably integrated microfluidics, to perform as biosensors. This is the first experimental assessment report of this type of radio frequency-based biosensor showing the real-time detection of PSA biomarkers

Learning and identification of wireless network internode dynamics using software defined radio

The recently developed paradigm of cognitive radio wireless devices has been developed with the goal of achieving more customizable and efficient spectrum utilization of commonly used wireless frequency bands. The primary focus of such spectrum utilization approaches has been to discern occupancies and vacancies over portions of the wireless spectrum without necessarily identifying how specific radio frequency (RF) devices contribute to the temporal dynamics of these occupancy patterns within the spectrum. The aim of this thesis is to utilize a hidden semi-Markov model (HSMM) statistical analysis to infer the individual occupancy patterns of specific users from wireless RF observation traces. It is proposed that the HSMM approach for RF device characterization over time may act as a first step towards performing a more complete characterization of the RF spectrum in which the inferred traffic patterns may demonstrate the coexistence of multiple networks, the specific devices comprising each distinct network, and the level of mutual interference between the component networks resultant from such coexistence. The first main portion of this thesis is the development of a Bayesian learning framework for HSMM characterization of the wireless RF observations, with occupancy periods and each individual RF device being classified as distinct states in the HSMM. The traditional HSMM approach is supplemented with the concept of the hierarchical Dirichlet random process to achieve a minimal number of states needed to effectively capture each distinct device, without the need for strong a priori assumptions regarding the number of devices seen in the RF trace prior to computational analysis. The second portion of the thesis utilizes user-programmed cognitive radios to construct a real-time software-defined RF network environment emulation testbed to assess the accuracy of the HSMM characterization. Finally, the HSMM algorithm is tested on wireless devices operating under an actual implementation of the ubiquitous IEEE 802.11 wireless standard

Development of a \u27Smart Glove\u27 Monitoring System for Personal Protective Equipment Applications

A proof of concept prototype of a smart glove system, which could monitor the physiological stresses related to repetitive strain and vibration-induced injuries, was developed at the University of Limerick Enterprise Research Centre in Ireland. The device logged grip force, vibration and goniometry data and could alert the user if dangerous vibration levels were reached. This prototype will provide a basis for future developments of devices that would enable safety by providing more information about injury risk in the workplace

GNSS array-based acquisition: theory and implementation

This Dissertation addresses the signal acquisition problem using antenna arrays in the general framework of Global Navigation Satellite Systems (GNSS) receivers. The term GNSS classi es those navigation systems based on a constellation of satellites, which emit ranging signals useful for positioning. Although the American GPS is already available, which coexists with the renewed Russian Glonass, the forthcoming European contribution (Galileo) along with the Chinese Compass will be operative soon. Therefore, a variety of satellite constellations and signals will be available in the next years. GNSSs provide the necessary infrastructures for a myriad of applications and services that demand a robust and accurate positioning service. The positioning availability must be guaranteed all the time, specially in safety-critical and mission-critical services. Examining the threats against the service availability, it is important to take into account that all the present and the forthcoming GNSSs make use of Code Division Multiple Access (CDMA) techniques. The ranging signals are received with very low precorrelation signal-to-noise ratio (in the order of ���22 dB for a receiver operating at the Earth surface). Despite that the GNSS CDMA processing gain o ers limited protection against Radio Frequency interferences (RFI), an interference with a interference-to-signal power ratio that exceeds the processing gain can easily degrade receivers' performance or even deny completely the GNSS service, specially conventional receivers equipped with minimal or basic level of protection towards RFIs. As a consequence, RFIs (either intentional or unintentional) remain as the most important cause of performance degradation. A growing concern of this problem has appeared in recent times. Focusing our attention on the GNSS receiver, it is known that signal acquisition has the lowest sensitivity of the whole receiver operation, and, consequently, it becomes the performance bottleneck in the presence of interfering signals. A single-antenna receiver can make use of time and frequency diversity to mitigate interferences, even though the performance of these techniques is compromised in low SNR scenarios or in the presence of wideband interferences. On the other hand, antenna arrays receivers can bene t from spatial-domain processing, and thus mitigate the e ects of interfering signals. Spatial diversity has been traditionally applied to the signal tracking operation of GNSS receivers. However, initial tracking conditions depend on signal acquisition, and there are a number of scenarios in which the acquisition process can fail as stated before. Surprisingly, to the best of our knowledge, the application of antenna arrays to GNSS signal acquisition has not received much attention. This Thesis pursues a twofold objective: on the one hand, it proposes novel arraybased acquisition algorithms using a well-established statistical detection theory framework, and on the other hand demonstrates both their real-time implementation feasibility and their performance in realistic scenarios. The Dissertation starts with a brief introduction to GNSS receivers fundamentals, providing some details about the navigation signals structure and the receiver's architecture of both GPS and Galileo systems. It follows with an analysis of GNSS signal acquisition as a detection problem, using the Neyman-Pearson (NP) detection theory framework and the single-antenna acquisition signal model. The NP approach is used here to derive both the optimum detector (known as clairvoyant detector ) and the sov called Generalized Likelihood Ratio Test (GLRT) detector, which is the basis of almost all of the current state-of-the-art acquisition algorithms. Going further, a novel detector test statistic intended to jointly acquire a set of GNSS satellites is obtained, thus reducing both the acquisition time and the required computational resources. The eff ects of the front-end bandwidth in the acquisition are also taken into account. Then, the GLRT is extended to the array signal model to obtain an original detector which is able to mitigate temporally uncorrelated interferences even if the array is unstructured and moderately uncalibrated, thus becoming one of the main contributions of this Dissertation. The key statistical feature is the assumption of an arbitrary and unknown covariance noise matrix, which attempts to capture the statistical behavior of the interferences and other non-desirable signals, while exploiting the spatial dimension provided by antenna arrays. Closed form expressions for the detection and false alarm probabilities are provided. Performance and interference rejection capability are modeled and compared both to their theoretical bound. The proposed array-based acquisition algorithm is also compared to conventional acquisition techniques performed after blind null-steering beamformer approaches, such as the power minimization algorithm. Furthermore, the detector is analyzed under realistic conditions, accounting for the presence of errors in the covariance matrix estimation, residual Doppler and delay errors, and signal quantization e ects. Theoretical results are supported by Monte Carlo simulations. As another main contribution of this Dissertation, the second part of the work deals with the design and the implementation of a novel Field Programmable Gate Array (FPGA)-based GNSS real-time antenna-array receiver platform. The platform is intended to be used as a research tool tightly coupled with software de ned GNSS receivers. A complete signal reception chain including the antenna array and the multichannel phase-coherent RF front-end for the GPS L1/ Galileo E1 was designed, implemented and tested. The details of the digital processing section of the platform, such as the array signal statistics extraction modules, are also provided. The design trade-o s and the implementation complexities were carefully analyzed and taken into account. As a proof-of-concept, the problem of GNSS vulnerability to interferences was addressed using the presented platform. The array-based acquisition algorithms introduced in this Dissertation were implemented and tested under realistic conditions. The performance of the algorithms were compared to single antenna acquisition techniques, measured under strong in-band interference scenarios, including narrow/wide band interferers and communication signals. The platform was designed to demonstrate the implementation feasibility of novel array-based acquisition algorithms, leaving the rest of the receiver operations (mainly, tracking, navigation message decoding, code and phase observables, and basic Position, Velocity and Time (PVT) solution) to a Software De ned Radio (SDR) receiver running in a personal computer, processing in real-time the spatially- ltered signal sample stream coming from the platform using a Gigabit Ethernet bus data link. In the last part of this Dissertation, we close the loop by designing and implementing such software receiver. The proposed software receiver targets multi-constellation/multi-frequency architectures, pursuing the goals of e ciency, modularity, interoperability, and exibility demanded by user domains that require non-standard features, such as intermediate signals or data extraction and algorithms interchangeability. In this context, we introduce an open-source, real-time GNSS software de ned receiver (so-named GNSS-SDR) that contributes with several novel features such as the use of software design patterns and shared memory techniques to manage e ciently the data ow between receiver blocks, the use of hardware-accelerated instructions for time-consuming vector operations like carrier wipe-o and code correlation, and the availability to compile and run on multiple software platforms and hardware architectures. At this time of writing (April 2012), the receiver enjoys of a 2-dimensional Distance Root Mean Square (DRMS) error lower than 2 meters for a GPS L1 C/A scenario with 8 satellites in lock and a Horizontal Dilution Of Precision (HDOP) of 1.2.Esta tesis aborda el problema de la adquisición de la señal usando arrays de antenas en el marco general de los receptores de Sistemas Globales de Navegación por Satélite (GNSS). El término GNSS engloba aquellos sistemas de navegación basados en una constelación de satélites que emiten señales útiles para el posicionamiento. Aunque el GPS americano ya está disponible, coexistiendo con el renovado sistema ruso GLONASS, actualmente se está realizando un gran esfuerzo para que la contribución europea (Galileo), junto con el nuevo sistema chino Compass, estén operativos en breve. Por lo tanto, una gran variedad de constelaciones de satélites y señales estarán disponibles en los próximos años. Estos sistemas proporcionan las infraestructuras necesarias para una multitud de aplicaciones y servicios que demandan un servicio de posicionamiento confiable y preciso. La disponibilidad de posicionamiento se debe garantizar en todo momento, especialmente en los servicios críticos para la seguridad de las personas y los bienes. Cuando examinamos las amenazas de la disponibilidad del servicio que ofrecen los GNSSs, es importante tener en cuenta que todos los sistemas presentes y los sistemas futuros ya planificados hacen uso de técnicas de multiplexación por división de código (CDMA). Las señales transmitidas por los satélites son recibidas con una relación señal-ruido (SNR) muy baja, medida antes de la correlación (del orden de -22 dB para un receptor ubicado en la superficie de la tierra). A pesar de que la ganancia de procesado CDMA ofrece una protección inherente contra las interferencias de radiofrecuencia (RFI), esta protección es limitada. Una interferencia con una relación de potencia de interferencia a potencia de la señal que excede la ganancia de procesado puede degradar el rendimiento de los receptores o incluso negar por completo el servicio GNSS. Este riesgo es especialmente importante en receptores convencionales equipados con un nivel mínimo o básico de protección frente las RFIs. Como consecuencia, las RFIs (ya sean intencionadas o no intencionadas), se identifican como la causa más importante de la degradación del rendimiento en GNSS. El problema esta causando una preocupación creciente en los últimos tiempos, ya que cada vez hay más servicios que dependen de los GNSSs Si centramos la atención en el receptor GNSS, es conocido que la adquisición de la señal tiene la menor sensibilidad de todas las operaciones del receptor, y, en consecuencia, se convierte en el factor limitador en la presencia de señales interferentes. Un receptor de una sola antena puede hacer uso de la diversidad en tiempo y frecuencia para mitigar las interferencias, aunque el rendimiento de estas técnicas se ve comprometido en escenarios con baja SNR o en presencia de interferencias de banda ancha. Por otro lado, los receptores basados en múltiples antenas se pueden beneficiar del procesado espacial, y por lo tanto mitigar los efectos de las señales interferentes. La diversidad espacial se ha aplicado tradicionalmente a la operación de tracking de la señal en receptores GNSS. Sin embargo, las condiciones iniciales del tracking dependen del resultado de la adquisición de la señal, y como hemos visto antes, hay un número de situaciones en las que el proceso de adquisición puede fallar. En base a nuestro grado de conocimiento, la aplicación de los arrays de antenas a la adquisición de la señal GNSS no ha recibido mucha atención, sorprendentemente. El objetivo de esta tesis doctoral es doble: por un lado, proponer nuevos algoritmos para la adquisición basados en arrays de antenas, usando como marco la teoría de la detección de señal estadística, y por otro lado, demostrar la viabilidad de su implementación y ejecución en tiempo real, así como su medir su rendimiento en escenarios realistas. La tesis comienza con una breve introducción a los fundamentos de los receptores GNSS, proporcionando algunos detalles sobre la estructura de las señales de navegación y la arquitectura del receptor aplicada a los sistemas GPS y Galileo. Continua con el análisis de la adquisición GNSS como un problema de detección, aplicando la teoría del detector Neyman-Pearson (NP) y el modelo de señal de una única antena. El marco teórico del detector NP se utiliza aquí para derivar tanto el detector óptimo (conocido como detector clarividente) como la denominada Prueba Generalizada de la Razón de Verosimilitud (en inglés, Generalized Likelihood Ratio Test (GLRT)), que forma la base de prácticamente todos los algoritmos de adquisición del estado del arte actual. Yendo más lejos, proponemos un nuevo detector diseñado para adquirir simultáneamente un conjunto de satélites, por lo tanto, obtiene una reducción del tiempo de adquisición y de los recursos computacionales necesarios en el proceso, respecto a las técnicas convencionales. El efecto del ancho de banda del receptor también se ha tenido en cuenta en los análisis. A continuación, el detector GLRT se extiende al modelo de señal de array de antenas para obtener un detector nuevo que es capaz de mitigar interferencias no correladas temporalmente, incluso utilizando arrays no estructurados y moderadamente descalibrados, convirtiéndose así en una de las principales aportaciones de esta tesis. La clave del detector es asumir una matriz de covarianza de ruido arbitraria y desconocida en el modelo de señal, que trata de captar el comportamiento estadístico de las interferencias y otras señales no deseadas, mientras que utiliza la dimensión espacial proporcionada por los arrays de antenas. Se han derivado las expresiones que modelan las probabilidades teóricas de detección y falsa alarma. El rendimiento del detector y su capacidad de rechazo a interferencias se han modelado y comparado con su límite teórico. El algoritmo propuesto también ha sido comparado con técnicas de adquisición convencionales, ejecutadas utilizando la salida de conformadores de haz que utilizan algoritmos de filtrado de interferencias, como el algoritmo de minimización de la potencia. Además, el detector se ha analizado bajo condiciones realistas, representadas con la presencia de errores en la estimación de covarianzas, errores residuales en la estimación del Doppler y el retardo de señal, y los efectos de la cuantificación. Los resultados teóricos se apoyan en simulaciones de Monte Carlo. Como otra contribución principal de esta tesis, la segunda parte del trabajo trata sobre el diseño y la implementación de una nueva plataforma para receptores GNSS en tiempo real basados en array de antenas que utiliza la tecnología de matriz programable de puertas lógicas (en ingles Field Programmable Gate Array (FPGA)). La plataforma está destinada a ser utilizada como una herramienta de investigación estrechamente acoplada con receptores GNSS definidos por software. Se ha diseñado, implementado y verificado la cadena completa de recepción, incluyendo el array de antenas y el front-end multi-canal para las señales GPS L1 y Galileo E1. El documento explica en detalle el procesado de señal que se realiza, como por ejemplo, la implementación del módulo de extracción de estadísticas de la señal. Los compromisos de diseño y las complejidades derivadas han sido cuidadosamente analizadas y tenidas en cuenta. La plataforma ha sido utilizada como prueba de concepto para solucionar el problema presentado de la vulnerabilidad del GNSS a las interferencias. Los algoritmos de adquisición introducidos en esta tesis se han implementado y probado en condiciones realistas. El rendimiento de los algoritmos se comparó con las técnicas de adquisición basadas en una sola antena. Se han realizado pruebas en escenarios que contienen interferencias dentro de la banda GNSS, incluyendo interferencias de banda estrecha y banda ancha y señales de comunicación. La plataforma fue diseñada para demostrar la viabilidad de la implementación de nuevos algoritmos de adquisición basados en array de antenas, dejando el resto de las operaciones del receptor (principalmente, los módulos de tracking, decodificación del mensaje de navegación, los observables de código y fase, y la solución básica de Posición, Velocidad y Tiempo (PVT)) a un receptor basado en el concepto de Radio Definida por Software (SDR), el cual se ejecuta en un ordenador personal. El receptor procesa en tiempo real las muestras de la señal filltradas espacialmente, transmitidas usando el bus de datos Gigabit Ethernet. En la última parte de esta Tesis, cerramos ciclo diseñando e implementando completamente este receptor basado en software. El receptor propuesto está dirigido a las arquitecturas de multi-constalación GNSS y multi-frecuencia, persiguiendo los objetivos de eficiencia, modularidad, interoperabilidad y flexibilidad demandada por los usuarios que requieren características no estándar, tales como la extracción de señales intermedias o de datos y intercambio de algoritmos. En este contexto, se presenta un receptor de código abierto que puede trabajar en tiempo real, llamado GNSS-SDR, que contribuye con varias características nuevas. Entre ellas destacan el uso de patrones de diseño de software y técnicas de memoria compartida para administrar de manera eficiente el uso de datos entre los bloques del receptor, el uso de la aceleración por hardware para las operaciones vectoriales más costosas, como la eliminación de la frecuencia Doppler y la correlación de código, y la disponibilidad para compilar y ejecutar el receptor en múltiples plataformas de software y arquitecturas de hardware. A fecha de la escritura de esta Tesis (abril de 2012), el receptor obtiene un rendimiento basado en la medida de la raíz cuadrada del error cuadrático medio en la distancia bidimensional (en inglés, 2-dimensional Distance Root Mean Square (DRMS) error) menor de 2 metros para un escenario GPS L1 C/A con 8 satélites visibles y una dilución de la precisión horizontal (en inglés, Horizontal Dilution Of Precision (HDOP)) de 1.2

Intrinsic dimensionality in vision: Nonlinear filter design and applications

Biological vision and computer vision cannot be treated independently anymore. The digital revolution and the emergence of more and more sophisticated technical applications caused a symbiosis between the two communities. Competitive technical devices challenging the human performance rely increasingly on algorithms motivated by the human vision system. On the other hand, computational methods can be used to gain a richer understanding of neural behavior, e.g. the behavior of populations of multiple processing units. The relations between computational approaches and biological findings range from low level vision to cortical areas being responsible for higher cognitive abilities. In early stages of the visual cortex cells have been recorded which could not be explained by the standard approach of orientation- and frequency-selective linear filters anymore. These cells did not respond to straight lines or simple gratings but they fired whenever a more complicated stimulus, like a corner or an end-stopped line, was presented within the receptive field. Using the concept of intrinsic dimensionality, these cells can be classified as intrinsic-two-dimensional systems. The intrinsic dimensionality determines the number of degrees of freedom in the domain which is required to completely determine a signal. A constant image has dimension zero, straight lines and trigonometric functions in one direction have dimension one, and the remaining signals, which require the full number of degrees of freedom, have the dimension two. In this term the reported cells respond to two dimensional signals only. Motivated by the classical approach, which can be realized by orientation- and frequency-selective Gabor-filter functions, a generalized Gabor framework is developed in the context of second-order Volterra systems. The generalized Gabor approach is then used to design intrinsic two-dimensional systems which have the same selectivity properties like the reported cells in early visual cortex. Numerical cognition is commonly assumed to be a higher cognitive ability of humans. The estimation of the number of things from the environment requires a high degree of abstraction. Several studies showed that humans and other species have access to this abstract information. But it is still unclear how this information can be extracted by neural hardware. If one wants to deal with this issue, one has to think about the immense invariance property of number. One can apply a high number of operations to objects which do not change its number. In this work, this problem is considered from a topological perspective. Well known relations between differential geometry and topology are used to develop a computational model. Surprisingly, the resulting operators providing the features which are integrated in the system are intrinsic-two-dimensional operators. This model is used to conduct standard number estimation experiments. The results are then compared to reported human behavior. The last topic of this work is active object recognition. The ability to move the information gathering device, like humans can move their eyes, provides the opportunity to choose the next action. Studies of human saccade behavior suggest that this is not done in a random manner. In order to decrease the time an active object recognition system needs to reach a certain level of performance, several action selection strategies are investigated. The strategies considered within this work are based on information theoretical and probabilistic concepts. These strategies are finally compared to a strategy based on an intrinsic-two-dimensional operator. All three topics are investigated with respect to their relation to the concept of intrinsic dimensionality from a mathematical point of view

Classical ghost imaging with opto-electronic light sources: novel and highly incoherent concepts

In conventional imaging systems, the emitted light from a source interacts with an object and the intensity of the transmitted or reflected light is captured by a spatially resolving detector. In this thesis, a fundamentally different imaging principle has been studied, known as ghost imaging (GI). In contrast to conventional imaging, GI exploits the intensity correlations of light to form an image of an object. A ghost image is obtained by measuring the total intensity of the transmitted or reflected light of an illuminated object and the spatially resolved intensity of a highly-correlated reference beam which itself has never interacted with the object. The information of both intensities alone is not enough to form an image of the object. However, image reconstruction can be achieved by correlating the two intensities. Intriguingly, the spatial resolution of the ghost image is provided by the non-interacting reference beam. The work presented in this thesis joins into the continuous strive for making GI applicable to real-world sensing and imaging fields. The title: Classical ghost imaging with opto-electronic emitters, reflects one of the approaches to this objective. The second approach is what rather sets this thesis apart from other ongoing work on GI. Instead of utilizing state-of-the-art detection systems, novel GI configurations are developed

NASA Tech Briefs, June 1996

Topics: New Computer Hardware; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Mathematics and Information Sciences;Books and Reports

Scaling full seismic waveform inversions

The main goal of this research study is to scale full seismic waveform inversions using the adjoint-state method to the data volumes that are nowadays available in seismology. Practical issues hinder the routine application of this, to a certain extent theoretically well understood, method. To a large part this comes down to outdated or flat out missing tools and ways to automate the highly iterative procedure in a reliable way. This thesis tackles these issues in three successive stages. It first introduces a modern and properly designed data processing framework sitting at the very core of all the consecutive developments. The ObsPy toolkit is a Python library providing a bridge for seismology into the scientific Python ecosystem and bestowing seismologists with effortless I/O and a powerful signal processing library, amongst other things. The following chapter deals with a framework designed to handle the specific data management and organization issues arising in full seismic waveform inversions, the Large-scale Seismic Inversion Framework. It has been created to orchestrate the various pieces of data accruing in the course of an iterative waveform inversion. Then, the Adaptable Seismic Data Format, a new, self-describing, and scalable data format for seismology is introduced along with the rationale why it is needed for full waveform inversions in particular and seismology in general. Finally, these developments are put into service to construct a novel full seismic waveform inversion model for elastic subsurface structure beneath the North American continent and the Northern Atlantic well into Europe. The spectral element method is used for the forward and adjoint simulations coupled with windowed time-frequency phase misfit measurements. Later iterations use 72 events, all happening after the USArray project has commenced, resulting in approximately 150`000 three components recordings that are inverted for. 20 L-BFGS iterations yield a model that can produce complete seismograms at a period range between 30 and 120 seconds while comparing favorably to observed data