摘要
针对重力数据不足的山区GNSS高程转换问题,该文选择区域适用性最优的全球重力场模型,利用剩余地形模型(RTM)改善其高频部分,通过测试和比较三次多项式曲面、多面函数、支持向量机拟合残余高程异常,得出3种方法对训练集点密度要求,采用顾及点位密度、分布和地形高差的建模点选取方法,拟合确定残余高程异常后可以获得较高精度的高程转换模型。实验结果显示,RTM对全球重力场模型平均改进为5.4 mm,精度提高约11%,残余高程异常确定后最终模型转换精度为2 cm,外部检核精度为2.8 cm,相比全球重力场经剩余地形模型改正精度提高约32%。
Aiming at the problem that it’s difficult to transform GNSS height in mountainous areas with insufficient gravity data,after selecting the global gravity field model with the best regional applicability,the residual terrain model(RTM)was used to improve the high-frequency part of the global gravity field model.Through the test and comparison of cubic polynomial surface,polyhedral function and support vector machine to fit the residual height anomaly,the requirements of the three methods for the training set point density were obtained.Using the modeling point selection method considering point density,distribution and topographic elevation difference,a high-precision height transformation model could be obtained after fitting the height anomaly.The experimental results showed that RTM improved the global gravity field model by 5.4 mm on average,with an improvement rate of 11%.After determining the residual height anomaly,the final height transformation model accuracy was 2 cm and the external validation accuracy was 2.8 cm,which was about 32%higher than that of the global gravity field corrected by the residual terrain model.
作者
周隽
罗旭
ZHOU Jun;LUO Xu(Chongqing Survey Institute,Chongqing 401121,China)
出处
《测绘科学》
CSCD
北大核心
2022年第10期74-81,共8页
Science of Surveying and Mapping
基金
重庆市技术创新与应用发展专项(cstc2021ycjh-bgzxm0321)
