Bayesian Methods in Geodetic Earth System Research

本研究为贝叶斯方法在大地测量系统研究中的应用奠定了基础。将开发一套算法和实施方案，以便在分析大地测量数据或将数据和物理模型输出相结合时制定贝叶斯估计，同时可以重用用于大地测量分析和模型集成的现有软件块。不确定性将由可能的非高斯概率密度函数严格表征。我们的工作将是通用的，而不局限于大地测量系统研究中的特定应用。然而，通过案例研究，我们将处理卫星重力数据的解释。

In the proposed study, we lay the foundations for the application of Bayesian methods in geodetic Earth system research. A bundle of algorithms and implementation schemes will be developed that allow to formulate Bayesian estimates when geodetic data is analysed or data and physical model output is to be combined, while existing software blocks for geodetic analysis and model integrations can be reused. Uncertainties will be strictly characterized by possibly non-Gaussian probability density functions. Numerically efficient algorithms will be developed, Our work will be generic and not restricted to a particular application within geodetic Earth system research. Yet, through case studies we will deal with the interpretation of satellite-gravimetric data.