超大观测网络及多GNSS系统的快速数据处理

Rapid Data Processing of Huge Networks and Multi-GNSS Constellation

采用IGS全球约110个多模观测站4周的观测数据，在不同采样间隔下进行精密定轨数据处理。分析了不同采样间隔下产品的精度以及数据处理的耗时情况。大量计算结果表明：①随着数据采样间隔的增加，数据处理时间呈线性减少的趋势。本文表明，采用15min采样间隔比5min采样间隔计算效率最多可以提高50％以上。②数据采样间隔的变化对轨道、钟差、ERP参数、参考框架等解算参数的影响很小。当采样间隔为5～10min时，基本上没有影响。为分析不同采样间隔产品对用户定位的影响，采用了全球22个测站4周的数据进行PPP静态定位，并且采用GRACE卫星1周的数据进行运动学精密定轨。采用不同轨道、钟差的静态结果表明，不同产品对水平方向精度的影响小于2mm，高程方向精度的影响小于6mm。GRACE卫星动态定位结果表明，不同产品对各个方向精度的影响小于1．5cm，三维位置的影响小于2cm。本文结论对于当前测站个数〉250的非差数据处理有拳考意义。

In the first part of the paper we discuss the challenges of huge networks and multi-GNSS da- ta processing for the zero-difference（ZD） strategy. Using 4 weeks＇ of data from global IGS GPS/ GLONASS stations, we performed daily data processing with data sampling ranging from 5-15 min. A comparison of the processing time and product precision under different sampling data shows： ① Computation efficiency is greatly improved by increasing data sampling; our results show the improve- ment of maximum 52%; ② Difference of product precision was marginally observed, and product pre- cision is almost the same when the sampling rate was changed from 5-10 min. To analyze the impact of different products on positioning applications, we performed PPP for 22 globally distributed IGS sta- tions and kinematic precise orbit determination for GRACE satellites using products generated from different data sampling procedures. Results show： ①Static PPP precision differs by less than 2 mm and 6 mm for the horizontal and height components, respectively; ②kinematic PPP precision differs by less than 1.5 cm for each coordinate component and less than 2 cm in three-dimensions.