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

Angular dispersion of radio waves in mobile channels

Multi-antenna techniques are an important solution for significantly increasing the bandwidth efficiency of mobile wireless data transmission systems. Effective and reliable design of these multi-antenna systems requires thorough knowledge of radiowave propagation in the urban environment. The aim of the work presented in this thesis is to obtain a better physical understanding of radiowave propagation in mobile radio channels in order to provide a basis for the improvement of radiowave propagation prediction techniques for urban environments using knowledge from 3-D propagation experiments and simulations combined with space-wave modelling. In particular, the work focusses on: the development of an advanced 3-D mobile channel sounding system, obtaining propagation measurement data from mobile radio propagation experiments, the analysis of measured data and the modelling of angular dispersive scattering effects for the improvement of deterministic propagation prediction models. The first part of the study presents the design, implementation and verification of a wideband high-resolution measurement system for the characterisation of angular dispersion in mobile channels. The system uses complex impulse response data obtained from a novel 3-D tilted-cross switched antenna array as input to an improved version of 3-D Unitary ESPRIT. It is capable of characterising the delay and angular properties of physically-nonstationary radio channels at moderate urban speeds with high resolution in both azimuth and elevation. For the first time, omnidirectional video data that were captured during the measurements are used in combination with the measurement results to accurately identify and relate the received radio waves directly to the actual environment while moving through it. The second part of the study presents the results of experiments in which the highresolution measurement system, described in the first part, is used in several mobile outdoor experiments in different scenarios. The objective of these measurements was to gain more knowledge in order to improve the understanding of radiowave propagation. From these results the dispersive effects in the angular domain, caused by rough building surfaces and other irregular structures was paid particular attention. These effects not only influence the total amount of received power in dense urban environments, but can also have a large impact on the performance and deployment of multi-antenna systems. To improve the data representation and support further data analysis a hierarchical clustering method is presented that can successfully identify clusters of multipath signal components in multidimensional data. By using the data obtained from an omnidirectional video camera the clusters can be related directly to the environment and the scattering effects of specific objects can be isolated. These results are important in order to improve and calibrate deterministic propagation models. In the third part of the study a new method is presented to account for the angular dispersion caused by irregular surfaces in ray-tracing based propagation prediction models. The method is based on assigning an effective roughness to specific surfaces. Unlike the conventional reflection reduction factor for Gaussian surfaces, that only reduces the ray power, the new method also distributes power in the angular domain. The results of clustered measurement data are used to calibrated the model and show that this leads to improved channel representations that are better matched to the real-world channel behavior

Long-term Information Preservation and Access

An unprecedented amount of information encompassing almost every facet of human activities across the world is generated daily in the form of zeros and ones, and that is often the only form in which such information is recorded. A good fraction of this information needs to be preserved for periods of time ranging from a few years to centuries. Consequently, the problem of preserving digital information over a long-term has attracted the attention of many organizations, including libraries, government agencies, scientific communities, and individual researchers. In this dissertation, we address three issues that are critical to ensure long-term information preservation and access. The first concerns the core requirement of how to guarantee the integrity of preserved contents. Digital information is in general very fragile because of the many ways errors can be introduced, such as errors introduced because of hardware and media degradation, hardware and software malfunction, operational errors, security breaches, and malicious alterations. To address this problem, we develop a new approach based on efficient and rigorous cryptographic techniques, which will guarantee the integrity of preserved contents with extremely high probability even in the presence of malicious attacks. Our prototype implementation of this approach has been deployed and actively used in the past years in several organizations, including the San Diego Super Computer Center, the Chronopolis Consortium, North Carolina State University, and more recently the Government Printing Office. Second, we consider another crucial component in any preservation system - searching and locating information. The ever-growing size of a long-term archive and the temporality of each preserved item introduce a new set of challenges to providing a fast retrieval of content based on a temporal query. The widely-used cataloguing scheme has serious scalability problems. The standard full-text search approach has serious limitations since it does not deal appropriately with the temporal dimension, and, in particular, is incapable of performing relevancy scoring according to the temporal context. To address these problems, we introduce two types of indexing schemes - a location indexing scheme, and a full-text search indexing scheme. Our location indexing scheme provides optimal operations for inserting and locating a specific version of a preserved item given an item ID and a time point, and our full-text search indexing scheme efficiently handles the scalability problem, supporting relevancy scoring within the temporal context at the same time. Finally, we address the problem of organizing inter-related data, so that future accesses and data exploration can be quickly performed. We, in particular, consider web contents, where we combine a link-analysis scheme with a graph partitioning scheme to put together more closely related contents in the same standard web archive container. We conduct experiments that simulate random browsing of preserved contents, and show that our data organization scheme greatly minimizes the number of containers needed to be accessed for a random browsing session. Our schemes have been tested against real-world data of significant scale, and validated through extensive empirical evaluations

Cooperative Position and Orientation Estimation with Multi-Mode Antennas

Robotic multi-agent systems are envisioned for planetary exploration and terrestrial applications. Autonomous operation of robots requires estimations of their positions and orientations, which are obtained from the direction-of-arrival (DoA) and the time-of-arrival (ToA) of radio signals exchanged among the agents. In this thesis, we estimate the signal DoA and ToA using a multi-mode antenna (MMA). An MMA is a single antenna element, where multiple orthogonal current modes are excited by different antenna ports. We provide a first study on the use of MMAs for cooperative position and orientation estimation, specifically exploring their DoA estimation capabilities. Assuming the agents of a cooperative network are equipped with MMAs, lower bounds on the achievable position and orientation accuracy are derived. We realize a gap between the theoretical lower bounds and real-world performance of a cooperative radio localization system, which is caused by imperfect antenna and transceiver calibration. Consequentially, we theoretically analyze in-situ antenna calibration, introduce an algorithm for the calibration of arbitrary multiport antennas and show its effectiveness by simulation. To also improve calibration during operation, we propose cooperative simultaneous localization and calibration (SLAC). We show that cooperative SLAC is able to estimate antenna responses and ranging biases of the agents together with their positions and orientations, leading to considerably better position and orientation accuracy. Finally, we validate the results from theory and simulation by experiments with robotic rovers equipped with software-defined radios (SDRs). In conclusion, we show that DoA estimation with an MMA is feasible, and accuracy can be improved by in-situ calibration and SLAC

Autonomous Swarm Navigation

Robotic swarm systems attract increasing attention in a wide variety of applications, where a multitude of self-organized robotic entities collectively accomplish sensing or exploration tasks. Compared to a single robot, a swarm system offers advantages in terms of exploration speed, robustness against single point of failures, and collective observations of spatio-temporal processes. Autonomous swarm navigation, including swarm self-localization, the localization of external sources, and swarm control, is essential for the success of an autonomous swarm application. However, as a newly emerging technology, a thorough study of autonomous swarm navigation is still missing. In this thesis, we systematically study swarm navigation systems, particularly emphasizing on their collective performance. The general theory of swarm navigation as well as an in-depth study on a specific swarm navigation system proposed for future Mars exploration missions are covered. Concerning swarm localization, a decentralized algorithm is proposed, which achieves a near-optimal performance with low complexity for a dense swarm network. Regarding swarm control, a position-aware swarm control concept is proposed. The swarm is aware of not only the position estimates and the estimation uncertainties of itself and the sources, but also the potential motions to enrich position information. As a result, the swarm actively adapts its formation to improve localization performance, without losing track of other objectives, such as goal approaching and collision avoidance. The autonomous swarm navigation concept described in this thesis is verified for a specific Mars swarm exploration system. More importantly, this concept is generally adaptable to an extensive range of swarm applications

NASA Tech Briefs, September 2012

Topics covered include: Beat-to-Beat Blood Pressure Monitor; Measurement Techniques for Clock Jitter; Lightweight, Miniature Inertial Measurement System; Optical Density Analysis of X-Rays Utilizing Calibration Tooling to Estimate Thickness of Parts; Fuel Cell/Electrochemical Cell Voltage Monitor; Anomaly Detection Techniques with Real Test Data from a Spinning Turbine Engine-Like Rotor; Measuring Air Leaks into the Vacuum Space of Large Liquid Hydrogen Tanks; Antenna Calibration and Measurement Equipment; Glass Solder Approach for Robust, Low-Loss, Fiber-to-Waveguide Coupling; Lightweight Metal Matrix Composite Segmented for Manufacturing High-Precision Mirrors; Plasma Treatment to Remove Carbon from Indium UV Filters; Telerobotics Workstation (TRWS) for Deep Space Habitats; Single-Pole Double-Throw MMIC Switches for a Microwave Radiometer; On Shaft Data Acquisition System (OSDAS); ASIC Readout Circuit Architecture for Large Geiger Photodiode Arrays; Flexible Architecture for FPGAs in Embedded Systems; Polyurea-Based Aerogel Monoliths and Composites; Resin-Impregnated Carbon Ablator: A New Ablative Material for Hyperbolic Entry Speeds; Self-Cleaning Particulate Prefilter Media; Modular, Rapid Propellant Loading System/Cryogenic Testbed; Compact, Low-Force, Low-Noise Linear Actuator; Loop Heat Pipe with Thermal Control Valve as a Variable Thermal Link; Process for Measuring Over-Center Distances; Hands-Free Transcranial Color Doppler Probe; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; PMA-Linked Fluorescence for Rapid Detection of Viable Bacterial Endospores; Portable Intravenous Fluid Production Device for Ground Use; Adaptation of a Filter Assembly to Assess Microbial Bioburden of Pressurant Within a Propulsion System; Multiplexed Force and Deflection Sensing Shell Membranes for Robotic Manipulators; Whispering Gallery Mode Optomechanical Resonator; Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles; Self-Sealing Wet Chemistry Cell for Field Analysis; General MACOS Interface for Modeling and Analysis for Controlled Optical Systems; Mars Technology Rover with Arm-Mounted Percussive Coring Tool, Microimager, and Sample-Handling Encapsulation Containerization Subsystem; Fault-Tolerant, Real-Time, Multi-Core Computer System; Water Detection Based on Object Reflections; SATPLOT for Analysis of SECCHI Heliospheric Imager Data; Plug-in Plan Tool v3.0.3.1; Frequency Correction for MIRO Chirp Transformation Spectroscopy Spectrum; Nonlinear Estimation Approach to Real-Time Georegistration from Aerial Images; Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications; Low-Cost Telemetry System for Small/Micro Satellites; Operator Interface and Control Software for the Reconfigurable Surface System Tri-ATHLETE; and Algorithms for Determining Physical Responses of Structures Under Load

Robust and Efficient Inference of Scene and Object Motion in Multi-Camera Systems

Multi-camera systems have the ability to overcome some of the fundamental limitations of single camera based systems. Having multiple view points of a scene goes a long way in limiting the influence of field of view, occlusion, blur and poor resolution of an individual camera. This dissertation addresses robust and efficient inference of object motion and scene in multi-camera and multi-sensor systems. The first part of the dissertation discusses the role of constraints introduced by projective imaging towards robust inference of multi-camera/sensor based object motion. We discuss the role of the homography and epipolar constraints for fusing object motion perceived by individual cameras. For planar scenes, the homography constraints provide a natural mechanism for data association. For scenes that are not planar, the epipolar constraint provides a weaker multi-view relationship. We use the epipolar constraint for tracking in multi-camera and multi-sensor networks. In particular, we show that the epipolar constraint reduces the dimensionality of the state space of the problem by introducing a ``shared'' state space for the joint tracking problem. This allows for robust tracking even when one of the sensors fail due to poor SNR or occlusion. The second part of the dissertation deals with challenges in the computational aspects of tracking algorithms that are common to such systems. Much of the inference in the multi-camera and multi-sensor networks deal with complex non-linear models corrupted with non-Gaussian noise. Particle filters provide approximate Bayesian inference in such settings. We analyze the computational drawbacks of traditional particle filtering algorithms, and present a method for implementing the particle filter using the Independent Metropolis Hastings sampler, that is highly amenable to pipelined implementations and parallelization. We analyze the implementations of the proposed algorithm, and in particular concentrate on implementations that have minimum processing times. The last part of the dissertation deals with the efficient sensing paradigm of compressing sensing (CS) applied to signals in imaging, such as natural images and reflectance fields. We propose a hybrid signal model on the assumption that most real-world signals exhibit subspace compressibility as well as sparse representations. We show that several real-world visual signals such as images, reflectance fields, videos etc., are better approximated by this hybrid of two models. We derive optimal hybrid linear projections of the signal and show that theoretical guarantees and algorithms designed for CS can be easily extended to hybrid subspace-compressive sensing. Such methods reduce the amount of information sensed by a camera, and help in reducing the so called data deluge problem in large multi-camera systems

Array communications in wireless sensor networks

Imperial Users onl