Geopotential Determination From Long-Arc Satellite-to-Satellite Tracking
N. Habana, Christopher Jekeli
Abstract
N. Habana, Christopher Jekeli
Abstract
One path to understanding the dynamics of our physical earth is to improve on recovery of the temporal gravity field. We test an innovative approach towards gravity inversion using Satellite-to-Satellite Tracking (SST) that can be applied to any arc length, originally proposed by (Xu, 2008). This, to the best of our knowledge has never been practically verified. However, alterations to the original formulae were performed to make the approach more numerically feasible. The new model is ideally suited to kinematic GNSS-determined orbits, and low-low SST observations, i.e. GRACE-type missions. It is a perturbation method based on Cartesian coordinates that is not subject to singularities that burden most conventional methods of gravity recovery from satellite tracking. Thus, geopotential parameter estimation will require significantly fewer unknowns in the normal equations compared to other techniques. Numerical analysis of this method shows that the model is viable up to the accuracy of our multi-step numerical integrator after a day-long orbit. It is then a straightforward process to estimate global/local parameters of the gravity field to deduce and monitor mass-flux on Earth’s surface and how it is affected by climate change.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
One path to understanding the dynamics of our physical earth is to improve on recovery of the temporal gravity field. We test an innovative approach towards gravity inversion using Satellite-to-Satellite Tracking (SST) that can be applied to any arc length, originally proposed by (Xu, 2008). This, to the best of our knowledge has never been practically verified. However, alterations to the original formulae were performed to make the approach more numerically feasible. The new model is ideally suited to kinematic GNSS-determined orbits, and low-low SST observations, i.e. GRACE-type missions. It is a perturbation method based on Cartesian coordinates that is not subject to singularities that burden most conventional methods of gravity recovery from satellite tracking. Thus, geopotential parameter estimation will require significantly fewer unknowns in the normal equations compared to other techniques. Numerical analysis of this method shows that the model is viable up to the accuracy of our multi-step numerical integrator after a day-long orbit. It is then a straightforward process to estimate global/local parameters of the gravity field to deduce and monitor mass-flux on Earth’s surface and how it is affected by climate change.
Key concepts: Satellite, Geopotential, Remote sensing, Geodesy, Satellite tracking, Tracking (education), Geology, Meteorology