Global gravity field recovery from satellite-to-satellite tracking data with the acceleration approach

Global gravity field recovery from satellite-to-satellite tracking data with the acceleration approachThis thesis is focused on the development of new techniques for global gravity field recovery from high-low (hl) and low-low (ll) satellite-to-satellite tracking (SST) data.There are a number of approaches to global gravity field recovery known from literature, including the variational equations approach, short arc approach, energy balance approach and acceleration approach.The focus of the thesis is the acceleration approach with an aim to produce high-quality global gravity field models using real data from CHAMP and GRACE satellite missions.In the first part, the research is devoted to a refinement of CHAMP hl-SST data processing methodology, which was developed at DEOS earlier.The refinement includes two major updates.The first update is usage of smoothed kinematic orbits, instead of reduced-dynamic ones, in data processing.A procedure based on B-splines has been developed for smoothing kinematic orbits by means of a regularised least-squares adjustment.The second update is the implementation of a data noise estimation procedure from the data themselves, with the aim to obtain a statistically optimal gravity field solution.The refined procedure is used to compute both regularised and a non-regularised models from a nearly one-year set of CHAMP accelerations.The regularized model is proved to be better than the regularized ITG-CHAMP01E model, and slightly better than the older DEOS CHAMP-01C 70 model computed at DEOS.The non-regularized solution is compared to a few non-regularized CHAMP-only models produced by several research groups.The comparison shows that the obtained solution clearly outperforms most of the alternative models.In the second part of the research, the methodology of processing CHAMP hl-SST data is extended to the case of GRACE hl-SST data, including the GRACE kinematic baselines.The kinematic positions and baselines are processed both individually and jointly.It is found that the kinematic baselines themselves are, in general, not favorable for the derivation of gravity field models.We explain this, first of all, by a poor sensitivity of the baseline data to East-West variations of the gravity field.Nevertheless, kinematic baselines slightly improve the quality xii