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The code observable of global navigation satellite systems (GNSS) is influenced by group delay variations (GDV) of transmitter and receiver antennas. For the Global Positioning System (GPS), the variations can sum up to 1 m in the ionosphere-free linear combination and thus can significantly affect precise code applications. The contribution of the GPS transmitters can amount to 0.8 m peak-to-peak over the entire nadir angle range. To verify the assumption of their time-invariance, we determined daily individual satellite GDV for GPS transmitter antennas over a period of more than two years. Dual-frequency observations of globally distributed reference stations and their multipath combination form the basis for our analysis. The resulting GPS GDV are stable on the level of a few centimeters for C1, P2, and for the ionosphere-free linear combination. Our study reveals that the inconsistencies of the GDV of space vehicle number (SVN) 55 with respect to earlier studies are not caused by temporal instabilities, but are rather related to receiver properties.

The code observable of global navigation satellite systems (GNSS) is influenced by group delay variations (GDV) of transmitter and receiver antennas. For the Global Positioning System (GPS), the variations can sum up to 1 m in the ionosphere-free linear combination and thus can significantly affect precise code applications. The contribution of the GPS transmitters can amount to 0.8 m peak-to-peak over the entire nadir angle range. To verify the assumption of their time-invariance, we determined daily individual satellite GDV for GPS transmitter antennas over a period of more than two years. Dual-frequency observations of globally distributed reference stations and their multipath combination form the basis for our analysis. The resulting GPS GDV are stable on the level of a few centimeters for C1, P2, and for the ionosphere-free linear combination. Our study reveals that the inconsistencies of the GDV of space vehicle number (SVN) 55 with respect to earlier studies are not caused by temporal instabilities, but are rather related to receiver properties.

A software GPS receiver is a functional GPS receiver in software. It has several advantages compared to its hardware counterparts. For instance, improvements in receiver architecture as well as GPS system structure can be easily adapted to it. Furthermore, interaction between nearby sensors can be coordinated easily. In this thesis, a SGR (software GPS receiver) is presented from a practical point of view. Major components of the SGR are implemented in Matlab environment. Furthermore, some alternative algorithms are implemented. SGR implementation is considered in two main sections namely a signal processing section and a navigation section. Signal processing section is driven by the raw GPS signal samples obtained from a GPS front-end of NordNavTM R-25 instrument. The conventional and the block adjustment of synchronizing signal (BAAS) processing methods are implemented and their performances are compared in terms of their speed and outputs. Signal processing section outputs raw GPS measurements and navigation data bits. Since the output data length is insufficient in our case, navigation section input is fed from AshtechTM GPS receiver for a moving platform and TrimbleTM GPS Receiver for a stationary platform. Satellite position computation, pseudorange corrections, Kalman filter and LSE (least squares estimation) are implemented in the navigation section. Kalman filter and LSE methods are compared in terms of positioning accuracy for a moving as well as a stationary platform. Results are compared with the commercial GPS outputs. This comparison shows that the software navigation section is equivalent to the commercial GPS in terms of positioning accuracy.

The L5 signal of the Global Positioning System (GPS) is becoming available on an increasing number of Block IIF satellites. As the third civilian signal, L5 is superior in signal design to the L1 C/A and L2C civilian signals. This new signal has been marked healthy for use on selected satellites since 2010, yet the hardware capable of tracking the L5 signal is still in the early stages of development. This work investigates the characteristics of the new signal and the quality of data produced by L5-tracking receivers. Commonly used receiver models chosen for this study are the Leica GRX1200+GNSS, the Trimble NetR8, and the Javad Delta TRE-G3TH. The metrics used in this analysis to assess the quality of data produced by these receivers are signal strength, receiver phase noise, receiver code noise, and multipath. The data used in these analyses were obtained from the International GNSS Service for the days of the year 275 to 281 in 2011. Metrics averaged over the GPS week 1656 provide a good indication of the overall performance of the receivers. / text

Les GNSS sont désormais largement présents dans le domaine des transports. Actuellement, la communauté scientifique désire développer des applications nécessitant une grande précision, disponibilité et intégrité.Ces systèmes offrent un service de position continu. Les performances sont définies par les paramètres du système mais également par l’environnement de propagation dans lequel se propagent les signaux. Les caractéristiques de propagation dans l’atmosphère sont connues. En revanche, il est plus difficile de prévoir l’impact de l’environnement proche de l’antenne, composé d’obstacles urbains. L’axe poursuivit par le LEOST et le LAGIS consiste à appréhender l’environnement et à utiliser cette information en complément de l’information GNSS. Cette approche vise à réduire le nombre de capteurs et ainsi la complexité du système et son coût. Les travaux de recherche menés dans le cadre de cette thèse permettent principalement de proposer des modélisations d'erreur de pseudodistances et des modélisations de l'état de réception encore plus réalistes. Après une étape de caractérisation de l’erreur, plusieurs modèles d’erreur de pseudodistance sont proposés. Ces modèles sont le mélange fini de gaussiennes et le mélange de processus de Dirichlet. Les paramètres du modèle sont estimés conjointement au vecteur d’état contenant la position grâce à une solution de filtrage adaptée comme le filtre particulaire Rao-Blackwellisé. L’évolution du modèle de bruit permet de s'adapter à l’environnement et donc de fournir une localisation plus précise. Les différentes étapes des travaux réalisés dans cette thèse ont été testées et validées sur données de simulation et réelles. / Today, the GNSS are largely present in the transport field. Currently, the scientific community aims to develop transport applications with a high accuracy, availability and integrity. These systems offer a continuous positioning service. Performances are defined by the system parameters but also by signal environment propagation. The atmosphere propagation characteristics are well known. However, it is more difficult to anticipate and analyze the impact of the propagation environment close to the antenna which can be composed, for instance, of urban obstacles or vegetation.Since several years, the LEOST and the LAGIS research axes are driven by the understanding of the propagation environment and its use as supplementary information to help the GNSS receiver to be more pertinent. This approach aims to reduce the number of sensors in the localisation system, and consequently reduces its complexity and cost. The work performed in this thesis is devoted to provide more realistic pseudorange error models and reception channel model. After, a step of observation error characterization, several pseudorange error models have been proposed. These models are the finite gaussian mixture model and the Dirichlet process mixture. The model parameters are then estimated jointly with the state vector containing position by using adapted filtering solution like the Rao-Blackwellized particle filter. The noise model evolution allows adapting to an urban environment and consequently providing a position more accurate.Each step of this work has been tested and evaluated on simulation data and real data.

Micro aerial vehicles and other autonomous systems have the potential to truly transform life as we know it, however much of the potential of autonomous systems remains unrealized because reliable navigation is still an unsolved problem with significant challenges. This dissertation presents solutions to many aspects of autonomous navigation. First, it presents ROSflight, a software and hardware architure that allows for rapid prototyping and experimentation of autonomy algorithms on MAVs with lightweight, efficient flight control. Next, this dissertation presents improvments to the state-of-the-art in optimal control of quadrotors by utilizing the error-state formulation frequently utilized in state estimation. It is shown that performing optimal control directly over the error-state results in a vastly more computationally efficient system than competing methods while also dealing with the non-vector rotation components of the state in a principled way. In addition, real-time robust flight planning is considered with a method to navigate cluttered, potentially unknown scenarios with real-time obstacle avoidance. Robust state estimation is a critical component to reliable operation, and this dissertation focuses on improving the robustness of visual-inertial state estimation in a filtering framework by extending the state-of-the-art to include better modeling and sensor fusion. Further, this dissertation takes concepts from the visual-inertial estimation community and applies it to tightly-coupled GNSS, visual-inertial state estimation. This method is shown to demonstrate significantly more reliable state estimation than visual-inertial or GNSS-inertial state estimation alone in a hardware experiment through a GNSS-GNSS denied transition flying under a building and back out into open sky. Finally, this dissertation explores a novel method to combine measurements from multiple agents into a coherent map. Traditional approaches to this problem attempt to solve for the position of multiple agents at specific times in their trajectories. This dissertation instead attempts to solve this problem in a relative context, resulting in a much more robust approach that is able to handle much greater intial error than traditional approaches.