利用Vondrak组合滤波算法融合UT1和LOD数据  

Combining UT1 and LOD data with Vondrak combined filtering algorithm

作　　者：魏飞 高玉平[1,3] 陈少杰[4] 尹东山 WEI Fei;GAO Yuping;CHEN Shaojie;YIN Dongshan(National Time Service Center,Chinese Academy of Science,Xi'an 710600,China;University of Chinese Academy of Science,Beijing 100049,China;Key Laboratory of Time and Frequency Primary Standards,Chinese Academy of Science,Xi'an 710600,China;School of Geospatial Information,Information Engineering University,Zhengzhou 450000,China)

机构地区：[1]中国科学院国家授时中心,西安710600 [2]中国科学院大学,北京100049 [3]中国科学院时间频率基准重点实验室,西安710600 [4]信息工程大学地理空间信息学院,郑州450000

出　　处：《测绘科学》2023年第10期50-57,共8页Science of Surveying and Mapping

基　　金：国家自然科学基金项目(11973046,41804034)。

摘　　要：为了有效弥补VLBI观测数据在解算地球自转参数(ERP)中数据密度不足和GNSS解算中数据不稳定的缺点,提高UT1数据的解算精度,本文提出了一种利用Vondrak组合滤波算法将VLBI观测得到的UT1数据和GNSS观测得到的日长(LOD)数据进行融合。通过仿真分别确定VLBI UT1和GNSS LOD观测数据的平滑因子,并根据两种数据的观测精度确定其权重进行数据融合。实验表明:融合算法对于提高数据精度效果显著。为验证该实验方法的有效性,将IGS测量得到的UT1数据与GNSS测量的日长(LOD)数据进行融合达到了同样提高数据精度的效果。利用融合算法获取高精度地球自转参数(ERP)为我国独立自主地球自转(ERP)参数测量与服务提供了新的思路。In order to effectively compensate for the insufficient data density of VLBI and the instability of GNSS in solving Earth rotation parameters(ERP) and improve the accuracy of UT1 data, this paper proposes Vondrak combined filtering algorithm to fuse the length of day(LOD) obtained by GNSS and UT1 obtained by VLBI. Before fusion, the smoothing factors of UT1 and LOD observation data are determined by simulation and their weights are determined according to the observation accuracy of the two data. Experiments show that the fusion algorithm has a significant effect on improving data accuracy. In order to verify the effectiveness of this method, the UT1 data obtained by IGS and the length of day(LOD) data measured by GNSS are fused to achieve the same effect in improving the data accuracy. The use of fusion algorithm to obtain high-precision Earth's rotation parameters provides new ideas for China's independent Earth's rotation parameter measurement and service.

关 键 词：世界时(UT1) 日长变化(LOD) Vondrak组合滤波 平滑因子 均方差 

分 类 号：P228.43[天文地球—大地测量学与测量工程]