Land vehicle navigation is primarily dependent upon the Global Positioning System (GPS) which provides accurate navigation in open sky. However, in urban and rural canyons GPS accuracy degrades considerably. To help GPS in such scenarios, it is often integrated with inexpensive inertial sensors. Such sensors have complex stochastic errors which are difficult to mitigate. In the presence of speed measurements from land vehicle, a reduced number of inertial sensors can be used which improve performance and termed as the Reduced Inertial Sensor System (RISS). Existing low-cost RISS/GPS integrated algorithms have limited accuracy due to use of approximations in error models and employment of a Linearized Kalman Filter (LKF). This research developed an enhanced error model for RISS which was integrated with GPS using an Extended Kalman Filter (EKF) for improved navigation of land vehicles. The proposed system was tested on several road experiments and the results confirmed the sustainable performance of the system during long GPS outages. To further increase the accuracy, Differential GPS (DGPS) is employed where carrier phase measurements are typically used. This requires resolution of Integer Ambiguity (IA) that comes at computational and time expense. This research uses pseudorange measurements for DGPS which mitigate large biases due to atmospheric errors and obviate the resolution of IA. These measurements are integrated with the enhanced RISS to filter increased noise and help GPS during signal blockages. The performance of the proposed system was compared with two other algorithms employing undifferenced GPS measurements where atmospheric effects are mitigated using either the Klobuchar model or dual frequency receivers. The proposed system performed better than both the algorithms in positional accuracy, multipath and GPS outages. This research further explored the reduction of Time-to-Fix Ambiguities (TTFA) for land vehicle navigation. To reduce the TTFA through inertial aiding, previous research used high-end Inertial Measurement Units (IMUs). This research uses MEMS grade IMU by integrating the enhanced RISS with carrier phase measurements using EKF. This algorithm was also tested on three road trajectories and it was shown that this integration helps reduce the TTFA as compared to the GPS-only case when fewer satellites are visible. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2014-06-23 11:30:58.036

The complementary advantages of GPS and INS have been the principle driving factor to integrate these two navigation systems as an integrated GPS/INS system in various architectural forms to provide robust positioning. Although the loosely coupled and tightly coupled GPS/INS systems have been in existence for over a decade or two and performed reasonably well, nevertheless, the tracking performance was still a concern in non-benign environments such as dynamic scenarios, indoor environments, urban areas, under foliages etc., where the GPS tracking loops lose lock due to the signals being weak, subjected to excessive dynamics or completely blocked. The motivation of this research, therefore, was to address these limitations with an integrated GPS/Pseudolite/INS system using ultra-tight integration architecture. The main research contributions are summarised as below: (a) The performance of the tracking loops in dynamic scenarios were analysed in detail with both conventional and ultra-tight software receivers. The stochastic modelling of the INS-derived Doppler is of utmost importantance in enhancing the benefits of ultra-tight integration, and therefore, two popular stochastic techniques??? Gauss Markov (GM) and Autoregressive (AR), were investigated to model the Doppler signal. The simulation results demonstrate that the AR method is capable of producing better accuracies and is more efficient. The algorithms to determine the AR parameters (order and coefficients) were also provided. (b) The various mathematical relationships that elicit the understanding of the ultra-tightly integrated system were derived in detail. The Kalman filter design and its implementation were also provided. Various simulation and real-time experiments were conducted to study the performance of the filter, and the results confirm the underlying assumptions in the theoretical analyses and the mathematical derivations. Covariance analysis was also performed to study the convergence and stability effects of the filter. (c) Interpolator design using signal processing techniques were proposed to increase the sampling rate of the INS-derived Doppler. To efficiently realise the interpolator transfer function, two optimal techniques were investigated ??? Polyphase and Cascaded Integrator Comb (CIC), and our results show that CIC was more efficient than polyphase in accuracy and real-time implementations. (d) The integration of Pseudolites (PL) with INS in ultra-tight configuration was analysed for an indoor environment. The acquisition and tracking performances of ???Pseudolites-only??? and ???Pseudolite/INS??? modes were compared to study the impact of the inertial signals aiding. The results demonstrate that aiding of the inertial signals with the baseband loops (acquisition and tracking) improve the overall tracking performance. An overview on the effects of the pseudolite signal propagation is also given. (e) Simulation and real-time experiments have been conducted to evaluate the proposed algorithms and the overall design of the ultra-tightly integrated system. A comparison was also done between GPS/PL/INS and GPS/INS integrated systems to study the potential advantages of the pseudolite integration. The details of the field experiment are provided. The data from a real-time experiment was processed to further evaluate the robustness of the system. The results confirm that the developed mathematical models and algorithms are correct.

Thesis (Ph. D.)--Miami University, Dept. of Political Science, 2003. / Title from second page of PDF document. Includes bibliographical references (p. 106-117).

Researchers in artificial intelligence and agent technologies are presented with a massive array of various technologies that they might use for their research projects. It is difficult for researchers to test their theories effectively in the field. It takes a great deal of time to develop the platform on which the newly created agent will be tested, with little or no time left for troubleshooting and the investigation of further solutions. Every time a new technique or agent is researched, the agent has to be redeveloped from the ground up. This makes it difficult for researchers to compare their own theories with previously developed components. With the wide range of technologies and techniques available, there is no easy way to effectively make use of the various components, as each tool uses different technologies that cannot be combined easily. This dissertation outlines the new plug-in oriented agent architecture (POAA) and describes the agents that use the POAA. POAA agents make extensive use of functional and controller-based plug-ins in order to extend the functionality and behaviour of the agent. The architecture was designed to facilitate machine learning and agent mobility techniques. POAA agents are created by mounting newly created dynamic plug-in components into the static structure of the agent. The static structure of the agent serves as the basis of agent functionality and as the controller for the agent’s life cycle. The static and dynamic components of the POAA agent interact with each other in order to perform the agent’s required tasks. The use of plug-ins will greatly improve the effectiveness of researchers, as only a single, standard architecture will exist. Researchers only need design and develop the plug-in required for their specific agent to function as desired. This will also facilitate the comparison of various tools and methods, as only the components being reviewed need to be interchanged to measure system performance. The use of different plug-in architectures is also investigated. This includes deciding if the plug-in base will be configured at application run-time or at the time of application compilation. This dissertation focuses on techniques that will facilitate machine learning and agent mobility. For these purposes, extensive use is made of the machine learning tool WEKA developed by University of Waikato in New Zealand [Wi00]. The use of Java in the prototype will also facilitate the cross platform capability of the proposed agents. / Prof. E.M. Ehlers

A detailed understanding of fundamental material properties can be obtained through the study of atomic vibrations, performed experimentally with neutron scattering techniques and coupled with the two powerful new computational methodologies I have developed. The first approach involves phonon-based simulations of the pair distribution function - a histogram of localised atomic positions generated experimentally from total scattering data. This is used to reveal ordering behaviour, to validate interatomic models and localised structure, and to give insights into how far dynamic behaviour can be studied using total scattering techniques. Most importantly, the long-standing controversy over dynamic disorder in β-cristobalite is resolved using this technique. Inelastic neutron spectroscopy (INS) allows \emph{direct} study of vibrational modes through their interaction with the neutron beam, and is the experimental basis for the second strand of the new methodology. I have developed new simulation and refinement tools based on the next generation of spectrometers currently being commissioned at the ISIS pulsed neutron source. This allows a detailed powder spectroscopy study of cristobalite and vitreous silica demonstrating that the Bose peak and so-called 'fast sound' features can be derived from standard lattice dynamics in both the crystal and the amorphous counterpart, and allowing discussion of their origins. Given the controversy in the literature, this is a key result. The new methodology also encompasses refinement of interatomic models against powder INS data, with aluminium providing a successful test-case. A more complex example is seen in calcite, with experimental data collected during the commissioning of the new MERLIN spectrometer. Simulated one-phonon coherent INS spectra for the single crystal and powder (the latter including approximations to multi-phonon and multiple scatter) are fully convolved with experimental resolution functions. These are used in the analysis of the experimental data, yielding previously unpublished dispersion curves and soft mode information, as well as allowing the effectiveness of powder refinement of more complex materials to be assessed. Finally, I present further applications with technologically important materials - relaxor ferroelectrics and high temperature pnictide superconductors. The conclusions draw together the different strands of the work, discussing the importance of these new advances together with future developments and scientific applications.

This study deals with crystal orientation effect along with the effects of microstructure on the pile-ups which affect the nanoindentation measurements. Two metal classes, face centered cubic (FCC) and body centered cubic (BCC, are dealt with in the present study. The objective of this study was to find out the degree of inaccuracy induced in nanoindentation measurements by the inherent pile-ups and sink-ins. Also, it was the intention to find out how the formation of pile-ups is dependant upon the crystal structure and orientation of the plane of indentation. Nanoindentation, Nanovision, scanning electron microscopy, electron dispersive spectroscopy and electron backscattered diffraction techniques were used to determine the sample composition and crystal orientation. Surface topographical features like indentation pile-ups and sink-ins were measured and the effect of crystal orientation on them was studied. The results show that pile-up formation is not a random phenomenon, but is quite characteristic of the material. It depends on the type of stress imposed by a specific indenter, the depth of penetration, the microstructure and orientation of the plane of indentation. Pile-ups are formed along specific directions on a plane and this formation as well as the pile-up height and the contact radii with the indenter is dependant on the aforesaid parameters. These pile-ups affect the mechanical properties like elastic modulus and hardness measurements which are pivotal variables for specific applications in micro and nano scale devices.

Les travaux menés durant cette thèse ont pour objectif d’améliorer les performances des systèmes hybrides GNSS/MEMS. Ils se décomposent en deux parties distinctes : d’une part, le développement d’un ensemble de traitement capteurs cherchant à améliorer la mesure elle-même et d’autre part, l’optimisation des algorithmes d’hybridation pour les capteurs MEMS de Thales. Le traitement capteur consiste en l’estimation de l’accélération vraie (resp. la vitesse angulaire vraie) à partir de la sortie du capteur accélérométrique (resp. gyrométrique). Ce traitement a été réalisé en deux sous-étapes : 1) La calibration qui consiste en l’identification du système non-linéaire connaissant ses entrées et ses sorties. Les relations entrant en jeu dans le modèle étant linéaires vis-à-vis des paramètres, on peut alors résoudre cette partie du problème par l’estimateur des moindres carrés (après extension du vecteur comprenant les entrées afin qu’il comporte les non linéarités). 2) L’inversion du modèle qui a pour but d’estimer les entrées du modèle connaissant ses sorties et l’estimation des paramètres effectuée durant l’étape de calibration. Après formalisation de ce problème sous forme d’un modèle dynamique, la résolution se fera à l’aide d’algorithme type filtre de Kalman ou filtre particulaire. Les algorithmes d’hybridation ont pour but de localiser un mobile dans l’espace connaissant l’information issue des MEMS ainsi que celle apportée par le GPS. Cette partie peut également se décomposer en deux sous-problèmes : 1) Lorsque que les signaux GPS sont disponibles (cas nominal), le but est d’améliorer les méthodes de navigation hybride GPS/INS existantes (EKF, UKF, PF, …). Dans notre cas, la réflexion a portée sur une modélisation à l’ordre 2 des biais des capteurs MEMS et sur la fermeture de la boucle de navigation (correction de la centrale inertielle à l’aide des erreurs issues du filtre d’hybridation). 2) Dans des scénarii défavorables (multitrajet et masquage des signaux GPS), la qualité des capteurs MEMS ne permet pas d’obtenir des résultats de navigation satisfaisants. Un algorithme basé sur un réseau de neurones a donc été développé. Durant les phases où le GPS est disponible, cet algorithme permet d’apprendre l’erreur commise par la centrale inertielle en mode survie par rapport au résultat de navigation hybride. Le réseau de neurones ainsi appris fournira alors cet élément de correction en cas de perte de l’information GPS. Ces différentes méthodes ont permis d’accroître la précision de la navigation GNSS/MEMS aussi bien dans le cas nominal que lors de pertes du signal GPS / The goal of this thesis is to improve accuracy of GNSS/MEMS integrated navigation system. Two main parts can be distinguished in this thesis: first, sensor processing can be achieved to improve measurement accuracy and then, navigation algorithm can be optimized for the specific case of MEMS sensors. Sensor processing is the estimation of real acceleration (resp. real angular rate) from the one measured by accelerometer (resp. gyrometer). This processing have been realized in two steps: 1) Calibration: identification of the non-linear system describing sensors (resolved by Least Square method). 2) Model inversion: estimation of the input of the non-linear system, i.e. acceleration and/or angular rate (resolved by Kalman filtering). Navigation algorithm have then to locate an object in space from both GNSS and MEMS data. This part have been also realized in two steps: 1) If GNSS signals are available, the goal is to improve the existing GNSS/INS navigation schemes (2nd-order bias modeling of MEMS sensors). 2) If GNSS are not available (e.g. multipath or outage), a Neural Network based algorithm have been developped, which learn the error made by the inertial platform during the unavailability of GNSS signals. These different methods have allowed to improve accuracy of GNSS/MEMS inetgrated navigation system both for nominal case and degraded case

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18511号 / 医博第3931号 / 新制||医||1006(附属図書館) / 31397 / 京都大学大学院医学研究科医学専攻 / (主査)教授 川口 義弥, 教授 上本 伸二, 教授 稲垣 暢也 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

The work is focused on localization in wireless networks and localization using inertial measurement units. There is also included a theoretical analysis of used localization techniques. The work also describes how to create application for data collection, application for receiving and processing data and used database. In conclusion of this work is verifying the functionality of whole system.

For a launch vehicle, the Navigation System is responsible for determining the vehicle state and providing state and state derived information for Guidance and Controls. The accuracy required of the Navigation System by the vehicle is dependent upon the vehicle, vehicle mission, and other consideration, such as impact foot print. NASAs Ares I launch vehicle and SLS are examples of launch vehicles with are/where to employ inertial navigation systems. For an inertial navigation system, the navigation system accuracy is defined by the inertial instrument errors to a degree determined by the method of estimating the initial navigation state. Utilization of GPS aiding greatly reduces the accuracy required in inertial hardware to meet the same accuracy at orbit insertion. For a launch vehicle with lunar bound payload, the navigation accuracy can have large implications on propellant required to correct for state errors during trans-lunar injection.