摘要
在北斗变形监测应用中,多路径误差显著影响监测精度。传统方法如小波分析和经验模态分解(EMD)在提取多路径误差信号过程中,常受模态混叠等问题影响,限制了多路径误差改正精度的提升。将完全自适应噪声集合经验模态分解算法(CEEMDAN)引入北斗监测,实现多路径误差信号的有效提取,并借助半天球模型对多路径误差进行实时改正。实验结果显示,在DOY(123~129)期间,该模型显著提高坐标序列精度:均方根误差(RMS)在水平北向由0.83 cm改善至0.09 cm,水平东向由1.05 cm改善至0.13 cm,高程方向由7.27 cm改善至0.35 cm。此外,通过利用7天的半天球模型内插DOY 130的数据,验证了该方法的实时性和有效性,实现水平精度优于0.15 cm、高程精度优于0.35 cm的改正效果,RMS改善率在水平和高程方向分别优于93.5%和95.5%。
In the application of Beidou deformation monitoring,multipath error significantly affects the monitoring accuracy.Traditional methods such as wavelet analysis and empirical mode decomposition(EMD)are often affected by modal aliasing in the process of extracting multipath error signals,which limits the improvement of multipath error correction accuracy.The complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)was introduced into Beidou monitoring to extract multipath error signals effectively,and the hemispherical model was used for real-time correction of multipath errors.The experimental results show that the model significantly improves the accuracy of coordinate sequence during DOY(123~129):the root mean square error(RMS)was improved from 0.83 cm to 0.09 cm in horizontal north direction,from 1.05 cm to 0.13 cm in horizontal east direction and from 7.27 cm to 0.35 cm in vertical direction.In addition,the real-time performance and effectiveness of this method were verified by interpolating DOY 130 data with a 7-day hemispherical model.The corrected horizontal accuracy was better than 0.15 cm,the vertical accuracy was better than 0.35 cm,and the RMS improvement rates in the horizontal and vertical directions were higher than 93.5%and 95.5%respectively.
作者
孙博文
朱星盛
杨怀志
匡团结
张云龙
刘洪润
肖翔
SUN Bowen;ZHU Xingsheng;YANG Huaizhi;KUANG Tuanjie;ZHANG Yunlong;LIU Hongrun;XIAO Xiang(China Railway Design Corporation,Tianjin 300308,China;Key Laboratory of Rail Transit Navigation,Positioning and Spatio-Temporal Big Data Technology in Tianjin,Tianjin 300308,China;Beijing-Shanghai High Speed Railway Co.,Ltd.,Beijing 100038,China)
出处
《中国铁路》
北大核心
2024年第5期50-57,共8页
China Railway
基金
中国国家铁路集团有限公司科技研究开发计划项目(P2022X001)
天津市自然科学基金重点项目(23JCZDJC00670)
内蒙古自治区重点研发和成果转化计划项目(2023SKJHZ0269)
中国铁路设计集团有限公司科研开发项目(2023A0240102、2023A0253801、2023A0240105)。
关键词
京沪高铁
变形监测
多路径误差
CEEMDAN
半天球模型
实时修正
北斗系统
Beijing-Shanghai HSR
deformation monitoring
multipath error
CEEMDAN
hemispherical model
real-time correction
beidou system
