Titlebook: VI Hotine-Marussi Symposium on Theoretical and Computational Geodesy; IAG Symposium Wuhan, Peiliang Xu (Dr.),Jingnan Liu (Professor),Athana

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Do We Need New Gravity Field Recovery Techniques for the New Gravity Field Satellites?analysis of accumulated orbit perturbations of artificial satellites with different altitudes and orbit inclinations. This so-called differential orbit improvement technique required the analysis of rather long arcs of days to weeks; it was the adequate technique for satellite arcs poorly covered wi

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A Localizing Basis Functions Representation for Low–Low Mode SST and Gravity Gradients Observationsthan the usual global solutions. In order to derive regional solutions, so-called in-situ observations like line-of-sight accelerations or satellite gradiometry data are optimal, since they do not change, if the potential outside a infinitesimal neighborhood of the observation point changes. Therefo

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Gravity Field Modeling on the Basis of GRACE Range-Rate Combinationstly connects a linear combination of gravitational potential gradients with a linear combination of range-rate measurements at several successive epochs. The system of observation equations is solved in the least-squares sense by means of the pre-conditioned conjugate gradient method. Noise in range

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The Torus Approach in Spaceborne Gravimetryto so-called semi-analytical schemes that are usually classified as either space-wise or time-wise under certain approximations and assumptions. Both approaches are efficient in that they provide a block-diagonal structure of the normal matrix for the least squares adjustment. At the same time, both

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GRACE Gravity Model Derived by Energy Integral Methodsatellite tracking data are presented, in which a strict expression of the difference of kinetic energy between two satellites on the same orbit in terms of KBR range-rate observation value is given. Using GRACE data from the both satellite and energy integral method, a gravity model with max. degre

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Robust Estimation and Robust Re-Weighting in Satellite Gravity ModellingP, GRACE, and GOCE in the near future). The stochastic and the functional models of these data are not perfectly known beforehand, and the data quality may vary considerably in time. We have used variance component estimation to re-weight the data sets, using a fast Monte-Carlo-type algorithm. In ge

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