引用本文: 柯福阳, 王庆, 潘树国. 基于映射函数网络RTK的大气误差内插估计模型[J]. 武汉大学学报 ( 信息科学版), 2012, 37(1): 73-76.
KE Fuyang, WANG Qing, PAN Shuguo. Network RTK Atmosphere Error Interpolation Estimation Model Based on Mapping Function[J]. Geomatics and Information Science of Wuhan University, 2012, 37(1): 73-76.
 Citation: KE Fuyang, WANG Qing, PAN Shuguo. Network RTK Atmosphere Error Interpolation Estimation Model Based on Mapping Function[J]. Geomatics and Information Science of Wuhan University, 2012, 37(1): 73-76.

## Network RTK Atmosphere Error Interpolation Estimation Model Based on Mapping Function

• 摘要: 在比较分析已有内插模型的基础上,以卫星高度角、参考站高程、距离为变量,以大气映射函数为基本模型,提出了一种新的适用于高程差异大的大气误差内插模型。利用江苏连续运行参考站系统部分参考站数据,采用不同的内插模型进行处理、比较与分析。结果表明,对于高程差异大、卫星高度角小的用户站,映射函数估计方法、低阶曲面模型能够准确地估计出其与主参考站之间双差对流层误差,其最大均方差不超过2cm;映射函数估计双差电离层误差方法与低阶曲面模型、线性内插模型的估计精度相当。在以上4种方法的比较中,距离线性内插模型的估计精度最差,将近5cm。

Abstract: In order to avoid the conventional interpolation model unrelated with observations and improve the accuracy of network RTK atmosphere error interpolation,a new model suitable for atmosphere error estimation with large height difference is given based on atmosphere mapping function and conventional interpolation model,whose variables are satellite elevation,reference station height and distance respectively.Finally,different interpolation models are used to process observations of part reference stations of Jiangsu CORS for estimating atmosphere error.The results by comparison and analysis show that the new model will increase the accuracy of atmosphere error estimation effectively.One hand,mapping function estimation method and lower-order surface model can accurately estimate the double difference troposphere error between users and main reference station with less than 2cm in maximum mean square error.On the other hand,mapping function estimation method,lower-order surface model and linear interpolation method are equivalent in accuracy for double difference ionosphere estimation,but the accuracy of distance interpolation method is the worst with nearly 5 cm error.

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