基于多源重力场探测数据的联合反演理论与模型研制

充分考虑可公开获取的多源重力场探测数据的不同频谱特点，自主研制高分辨率重力场模型具有重要的科学意义和应用价值，可为大地测量学等地球科学研究提供重要数据支撑。本项目拟融合GRACE和GOCE卫星及新版测高重力异常等数据反演719阶次的重力场，主要内容：1.研究GOCE卫星重力梯度的时变重力场变化改正和粗差探测，实现由GOCE卫星 level 1b数据直接反演；2.分析新版GOCE卫星重力梯度误差特性，构建去相关ARMA滤波器，考虑不同观测时间段重力梯度精度，最大限度挖掘观测值信号；3.统一参考基准，法方程层面实现GRACE和GOCE卫星数据的最优融合；4.针对卫星重力、卫星测高等数据源具有不同精度和不同频谱的特点，构建重力场反演的完全法方程矩阵，采用最优权策略，精化函数模型，以实现多类重力场探测数据的互补与融合，反演高阶重力场，最后采用GNSS/水准等数据评估模型精度。

It is of great scientific significance and application value to independently develop a high-resolution gravity field model based on free multi-source gravity data with different spectrum characteristics, which can provide important data support for scientific research for geodesy and other Earth sciences. This project intends to combine GRACE, GOCE satellite data and the new version of altimetric gravity anomaly data to recover Earth gravity field model up to degree and order 719, and the main contents are as follows: 1.By studying the theory of GOCE satellite data preprocessing, including correction for temporal gravity field variations and outlier detection, the gravity field models are directly inverted from GOCE satellite level 1b data; 2.After analyzing the error characteristics of the new version of the GOCE gradient data, an efficient digital decorrelation ARMA filters are designed to maximize the observation signals, and the accuracy of gravity gradient data is considered at different observation time; 3.After unifying the reference datum, the GOCE and GRACE normal equations are combined by applying optimum weighting strategies; 4.The GRACE, GOCE satellite data and altimetric gravity anomaly data have different accuracy and different frequency spectrums, according to this characteristics, the full normal equations from different data are constructed and combined for recovering high-order gravity field model, and the stochastic modeling is refined by applying optimum weighting strategies , finally the accuracy of gravity field models are estimated by using GNSS / leveling data.