In recent years, the number of precise online DGNSS (Differential Global Navigation Satellite System) applications has significantly increased. Precise DGNSS correction services have been created that enable an online positioning with accuracy in the centimetre region. In contrast to the co-ordinates found by DGNSS, the measured height needs to be transformed. This is because national height systems refer to a physically defined Height Reference Surface, HRS, that approximates the mean sea level, while the height derived from DGNSS positioning is the height above the WGS84 (World Geodetic System 1984), a mathematical model of the earth and is therefore called "ellipsoidal height". So for the application of precise DGNSS services and for the generation of transformation messages, such as RTCM 3.0, there is an urgent need for a HRS, in a unified datum with appropriate accuracy. This thesis deals with the concept of the Digital FEM (Finite Element Method) Height Reference Surface, DFHRS. This concept enables the rigorous least squares adjustment of any HRS related observation. The HRS is modelled as continuous surface by a local Taylor-series expansion in a grid of FEM-meshes. With this, areas of any size may be computed. The theory of the DFHRS and further development of the mathematical model, especially the incorporation of observed gravity accelerations, are the main parts of this thesis. As the applied Taylor-series expansion of the DFHRS concept only holds for a twodimensional approximation, Spherical Cap Harmonics, SCH, had to be introduced as auxiliary parameter, to give a complete representation of the local gravity field. Spherical Cap Harmonics, SCH, may be interpreted as the general case of Spherical Harmonics, SH, that have been applied in geodetic applications for decades. The goal of the SCH coefficients, in contrast to the SH coefficients is that they may be applied over areas with limited extent. Due to numerical reasons, the combined least squares estimation of the DFHRS and the SCH coefficients in practical computations had to be done applying a sequential procedure. In practical examples, different HRS representations with centimetre accuracy were computed by combining GNSS/Levelling points and precise gravimetric geoid models according to the DFHRS concept. In a further example, gravity acceleration observations and a global geopotential model have been introduced into a combined least squares estimation of SCH coefficients. It could be shown that the introduction of the gravity accelerations leadsto a significant improvement of the representation of the local gravity field. To perform a two step adjustment, height anomalies were derived from the determined SCH coefficients and introduced together with GNSS/Levelling points into a second adjustment according to the DFHRS concept. By comparison with a reference model, the resulting accuracy of the HRS representation was estimated to be 0.025m.

Missions involving multiple spacecraft have become of great interest in the last decade as they offer a number of scientific and engineering advantages. Though already largely adopted for communication, geo-location (GPS) and meteorology purposes, only recently this paradigm is showing its potential benefits for Earth Observation and Space Exploration. Multiple platforms are crucial in the context of global monitoring and disaster management. The Global Monitoring for Environment and Security - GMES or the Disaster Monitoring constellation arc the first examples of this trend. From the mission planning point of view, the use of multiple platforms is opening new challenges to the automated planning & scheduling systems whose aim is gaining maximum value from the constellation by optimising the use of on-board resources and by coordinating the different spacecraft, Hence, new approaches arc needed to handle this level of complexity, The main goal of this research is the construction of a _ground-based automated planning & scheduling system for the imaging campaign of an Earth Observation constellation. The target mission is the Disaster Monitoring Constellation, which requires a system that is responsive to the asynchronous requests of different user groups with different priority levels, Multi agent sY8tems represent a fruitful approach to model such a dynamic context, The novelty of this project is to apply nature-inspired techniques, such as stigmergy, to achieve optimisation and coordination, This mechanism offers high-level of adaptability and 8calnbility allowing the system to find an efficient schedule at global -level due to the collaboration of alt the agents, A key novelty of this project is the development of a theoretical framework to model the self-organising long-term system's behaviours. This model is able to describe the architecture us a dynamical system. It offers new insights which are the basis of a new algorithm which regulates the trade-off of exploration/exploitation via changes in the system's stability. The theoretical model, as well as the algorithm, has been extended in order to include a coordination mechanism which is required by the multiple platform scenario. An empirical evaluation has been used to validate the system's capabilities in optimisation, adaptability and scalability in the case of dynamic problems for single and multiple spacecraft. Lastly, the transferability of the system developed has been demonstrated to different contexts outside the Earth Observation field such as the ESA GENSO (Global Educational Network for Satellite Operations) network. This is a ground station network sharing similar requirements with the Earth Observation constellation scenario.

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The primary aim of this research is to develop and assess the innovative methods and techniques which are used to augment GPS using a variety of digital spatial data. It is well known that the use of GPS can be severely compromised by various error sources such as signal obstructions, multipath and poor satellite geometry etc., especially in highly built-up areas. In order to improve the accuracy and reliability of GPS, complementary data is often combined with GPS data for enhancing the performance of a standalone GPS receiver. Spatial data is one type of complementary data that can be used to augment GPS. However, the potential of using various types of existing and newly acquired spatial data for enhancing GPS performance has not been fully realised. This is particularly true due to the fact that higher accuracy digital surface models (DSMs), which include buildings and vegetation, and digital maps, have only been made widely available in recent years. This thesis will report on a number of experiments that used spatial data of various complexity and accuracy for enhancing GPS performance. These experiments include height aiding with different scale digital terrain models (DTMs); map-matching using odometer data, DTM and road centrelines; modelling and prediction of GPS satellite visibility using DSMs; and prediction of GPS multipath effect using DSMs and building footprints. These experiments are closely related to each other in the sense that GPS and spatial data are combined to provide value-added information for improved modelling and prediction of GPS positioning accuracy and reliability, for applications such as transport navigation and tracking ... Extensive fieldwork has been carried out to verify the developed techniques and methods. The results show that the accuracy of a standalone GPS receiver can be improved by height aiding using a higher resolution DTM and map-matching especially when the satellite geometry is poor. The mean error of single receiver GPS positioning for one particular dataset, on which the described map-matching algorithm was developed, is 8.8m compared with 53.7m for GPS alone. This work was carried out in collaboration with London Transport. In terms of satellite visibility analysis, the results obtained from the fieldwork indicate that greater modelling accuracy has been achieved when using higher resolution DSMs. Furthermore, a ray tracing model was implemented in a 3D GIS environment in order to model reflected and diffracted GPS signals. The Double Differencing (DD) residuals were used to give an indication of the magnitude of the possible pseudorange multipath error caused by diffraction. A single-knife diffraction model was first implemented on 1m Light Detection And Ranging (LiDAR) DSMs, and verified by post-processing (i.e. large DD residuals occurred when the satellites are partially masked and unmasked by buildings), which indicate that GPS multipath prediction with LiDAR data and building footprints is feasible, and has the potential to offer greater modelling accuracy.