融合多源数据的局部重力场建模中线性化误差的研究

The Research on Linearization Errors in Regional Gravity Field Modeling Based on Heterogeneous Data Sets

引入高阶重力场模型作为参考场,削弱局部重力场逼近中线性化误差的影响。以实测的陆地重力异常、船载重力异常及航空重力扰动为基础数据,基于泊松小波径向基函数分析不同参考场对局部重力场逼近的影响。结果表明,引入高阶全球重力场模型代替GRS80参考椭球正常场作为参考场,能更为准确地逼近真实的重力场,有效削弱线性化误差的影响。相比于基于GRS80正常场构建的似大地水准面模型,基于DGM1S重力场模型为参考场构建的似大地水准面的精度,在地形起伏较大的德国、英国及挪威区域分别提高了1.5mm、3.3mm和9.0mm。

This paper studies the issues of linearization errors in regional gravity field modeling and introduces the high-order global gravity model as reference gravity field to reduce the corresponding linearization errors.As an example,we analyze the effects on regional gravity field modeling introduced by different reference gravity fields.To do so,we use Poisson wavelets radial basis functions based on terrestrial and shipboard gravity anomaly andon airborne gravity disturbance.The results show that the incorporation of global gravity field model,instead of GRS80-derived normal gravity field,as the reference gravity field leads a better approximation of the real gravity field.The corresponding linearization errors are also reduced.Compared to the quasi-geoid computed from the GRS80-derived normal gravity field,the accuracy of the quasi-geoid based on DGM1S-derived reference gravity field is improved by 1.5mm,3.3mm and 9.0mm at Germany,England and Norway respectively,where the topography show more undulation.