Simulation of Regional Gravity Field Recovery from Satellite Gravity Gradiometer Data Using Collocation and FFT

Abstract

When planning a satellite gravity gradiometer (SSG) mission, it is important to know the quality of quantities to be recovered at ground level as a function of e.g. satellite altitude, data type and sampling rate, and signal variance and noise. This kind of knowledge may be provided either using the formal error estimates of wanted quantities using least-squares collocation (LSC) or by comparing simulated data at ground level with results computed by methods like LSC or FFT.The GRAVSOFT-program package has been extended and upgrated in order to provide a general tool for the study of the quality of regional gravity field recovery from SSG data. Results of a regional gravity field recovery in a 10x20 area surrounding the Alps using LSC and FFT are reported. Data used as observations and for comparison at ground level were generated using the OSU 86F coefficient set, complete to degree 360. A covariance function which also included terms above degree 360 was used for prediction and error estimation. This had the effect, that the formal error standard deviations for gravity anomalies were considerably larger than the standard deviations of predicted minus simulated quantities. This shows the importance of using data with frequency content above degree 360 in simulation studies.In an appendix input and output examples are given for the various steps one have to make in order to complete a regional quality assessment. Hereby a “users guide” is provided, which may be used in further studies of satellite (or aircraft) gravity gradiometer missions.KeywordsSimulated DataGround LevelData TypeCovariance FunctionGravity AnomalyThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.