基于极点对称模态分解的GNSS测站速度估计方法
GNSS station velocity estimation method based on extrema symmetric mode decomposition
刘开红1
作者信息
- 1. 江西省地质局地理信息工程大队,江西 南昌 330001
- 折叠
摘要
全球导航卫星系统(GNSS)测站速度是描述地壳运动的重要指标.本研究旨在通过高精度分析方法提升地壳运动监测的精度,基于日本地区两个GNSS测站(G178和J753)2016年至2023年东(East,E)、北(North,N)和高程(Up,U)方向的坐标时间序列数据,创新性地融合了极点模态分解(ESMD)与最小二乘拟合技术,以优化E、N和U方向上的速度估计.结果显示:基于本文提出方法估计的G178测站N、E、U三个方向站速度分别为-1.69、-1.58、4.60 mm/a,估计残差分别为0.03、0.02、0.04 mm/a.J753测站N、E、U三个方向站速度分别为-5.13、15.62、7.17 mm/a,估计残差分别为0.14、0.04、0.08 mm/a.本文提出的站速度估计方法较传统最小二乘法方法估计精度提高了19.81%～67.24%,站速度的拟合度提高了0.7%～2.1%.此研究证实,所提方法有效提高了GNSS测站速度估计的精度,对于地壳运动监测具有重要的科学价值和实际应用意义.
Abstract
The velocities of global navigation satellite system(GNSS)stations are crucial indicators for describing crustal movement.This paper aimed to improve the precision of monitoring crustal movement through high-precision analysis methods.Based on the coordinate time series data in the east(E),north(N),and up(U)directions from two GNSS stations(G178 and J753)in Japan from 2016 to 2023,the extrema symmetric mode decomposition(ESMD)with least squares fitting technique was innovatively integrated to optimize the velocity estimation in the E,N,and U directions.The results show that the estimated velocities of station G178 in the N,E,and U directions are-1.69,-1.58 and 4.60 mm/a,respectively,with estimation residuals of 0.03,0.02 and 0.04 mm/a.For station J753,the velocities in the N,E,and U directions are-5.13,15.62 and 7.17 mm/a,respectively,with estimation residuals of 0.14,0.04 and 0.08 mm/a.The proposed station velocity estimation method in this paper improves the estimation precision by 19.81%-67.24%and the goodness of fit for station velocity by 0.7%-2.1%.This research confirms that the proposed method effectively enhances the precision of GNSS station velocity estimation,holding significant scientific value and practical implications for monitoring crustal movement.
关键词
极点对称模态分解(ESMD)/全球导航卫星系统(GNSS)/站速度/最小二乘拟合Key words
extrema symmetric mode decomposition(ESMD)/global navigation satellite system(GNSS)/station velocity/least squares fitting引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据