基于 EEMD 和 Husrt 指数的 GNSS 基准站的垂向速率估计

摘要

The daily coordinate time series of Global satellite navigation system (GNSS) reference stations contain the complex effects of noise signals ,non‐tectonic deformation and other factors ,particularly in the vertical direction ,of w hich the factors have a greater impact on the velocity estimation of GNSS reference station on the International Terrestrial Reference Frame (ITRF) .In order to improve the accuracy of the velocity estimation ,this paper uses the Ensemble Empirical Mode Decomposition (EEMD ) method to decompose the vertical time series of GNSS reference station ,and the noise signal ,seasonal signal and long‐term trend signal can be reconstructed respectively based on the Hurst value of signals .Then the vertical velocity can be estimated by using the least square method to fit the long‐term trend signals .By analyzing the vertical time series of GNSS stations of Crustal Movement Observation Network of China (CMONOC) from January 2001 to December 2013 ,the EEMD method and Husrt exponent based on the least square method can accurately estimate the vertical velocity of GNSS reference station .%连续的全球卫星导航系统（GNSS）基准站的坐标时间序列中包含了复杂的噪声信号、非构造形变及其它因素的影响，尤其在垂直方向，对GNSS基准站在国际地球参考框架（ITRF）下的运动速率估计产生了较大的干扰。为进一步提高速率精度，文中采用整体模态分解（EEMD）方法对GNSS基准站的垂向观测时间序列进行分解，并根据各种信号的Hurst值进行分类及重构为噪声信号、季节性信号和长期趋势信号，采用最小二乘方法拟合长期趋势信号得到垂向速率。通过对中国大陆构造环境监测网络（CMONOC）的GNSS台站从2001—2013年近13 a的垂向坐标时间序列的实例分析，采用基于EEMD和 Husrt指数的最小二乘法能够准确地估计GNSS基准站的垂向速率。