GPS/GLONASS/GALILEO实时服务（RTS）产品性能评估分析

目前,不同机构提供的GNSS实时服务产品性能存在差异。为了全面揭示实时服务产品的性能，为系统服务和用户应用提供参考，统计了各实时服务产品的历元完整率及卫星数量，基于实时轨道和钟差恢复方法，比较分析了产品精度，并评估了产品定位性能。研究结果表明：正常情况下，实时服务产品的历元完整率较高，基本可保持在95%以上，所提供系统的卫星数量保持稳定且充足。对于GPS，各机构卫星实时轨道平均精度基本一致，约为3cm，实时钟差精度略有差别。对于其他GNSS，不同机构产品精度存在差别。利用实时服务产品进行GPS实时精密单点定位的平面精度优于10cm，高程精度优于20cm。相对于GPS单系统，多系统联合定位精度基本一致，但收敛速度明显提升。     

Analysis of GNSS clock prediction performance with different interrupt intervals and application to real-time kinematic precise point positioning

Continuous and timely real-time satellite orbit and clock products are mandatory for real-time precise point positioning (RT-PPP). Real-time high-precision satellite orbit and clock products should be predicted within a short time in case of communication delay or connection breakdown in practical applications. For prediction, historical data describing the characteristics of the real-time orbit and clock can be used as the basis for performing the prediction. When historical data are scarce, it is difficult for many existing models to perform precise predictions. In this paper, a linear regression model is used to predict clock products. Seven-day GeoForschungsZentrum (GFZ) final clock products sampled at 30 s are used to analyze the characteristics of GNSS clocks. It is shown that the linear regression model can be used as the prediction model for the satellite clock products. In addition, the accuracy of the clock prediction for different satellites are analyzed using historical data with different periods (such as 2 and 10 epochs). Experimental results show that the accuracy of the clock with the linear regression prediction model using historical data with 10 epochs is 1.0 ns within 900 s. This is higher accuracy than that achieved using historical data of 2 epochs. Finally, the performance analysis for real-time kinematic precise point positioning (PPP) is provided using GFZ final clock prediction results and state space representation (SSR) clock prediction results when communication delay or connection breakdown occur. Experimental results show that the positioning accuracy without prediction is better than that with prediction in general, whether using the final clock product or the SSR clock product. For the final clock product, the positioning accuracy in the north (N), east (E), and up (U) directions is better than 10.0 cm with all visible GNSS satellites with prediction. In comparison, the 3D positioning accuracy of N, E, and U directions with visible GNSS satellites whose prediction accuracy is better than 0.1 ns using historical data of 10 epochs is improved from 15.0 cm to 7.0 cm. For the SSR clock product, the positioning accuracy of N, E, and U directions is better than 12.0 cm with visible GNSS satellites with prediction. In comparison, the 3D positioning accuracy of N, E, and U directions with visible GNSS satellites whose prediction accuracy is better than 0.1 ns using historical data of 10 epochs is improved from 12.0 cm to 9.0 cm.     

RTS平滑滤波在事后姿态确定中的应用

为了进一步提高卫星事后姿态确定的精度,基于EKF引入RTS后向平滑滤波.针对目前广泛使用的以误差作为状态变量的EKF姿态确定方法,不改变原有的EKF方法,通过对EKF过程中得到的数据做相应处理,在保证不出现协方差阵奇异的情况下,成功地将RTS平滑滤波算法应用到事后姿态确定中,并用RTS平滑滤波算法进行了仿真.仿真结果表明,RTS平滑滤波的姿态确定精度明显优于EKF.