一种CORS站高程序列非线性趋势项分析方法An analysis method of non-linear trend items in the high sequence of CORS stations
王志勇,王崇倡,刘宇晨,金泽林,焦亚沁
摘要(Abstract):
针对传统线性模型通过拟合连续运行参考站(CORS)高程时间序列趋势项,使CORS站运动趋势单一化导致无法体现测站各自运动特性的问题,该文提出一种基于CORS高程时间序列本身的非线性趋势项定量识别与估计方法。首先,用K均值聚类整体经验模态分解方法对CORS站高程时间序列进行分解;其次,基于排列熵理论进行非线性趋势项的定量识别与合成;最后,采用正弦函数模型、线性多项式模型、傅里叶模型对非线性趋势项进行建模拟合并讨论拟合精度。实验结果表明:基于排列熵的非线性趋势项定量识别方法避免了人为判别误差,准确地反映了序列自身的变化趋势;3种模型中,傅里叶模型拟合效果最佳。
关键词(KeyWords): CORS;非线性趋势项;K均值;排列熵;线性多项式模型;傅里叶模型;正弦函数模型
基金项目(Foundation): 国家自然科学基金项目(41471351)
作者(Author): 王志勇,王崇倡,刘宇晨,金泽林,焦亚沁
DOI: 10.16251/j.cnki.1009-2307.2022.04.006
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