LMD和小波阈值的GNSS坐标时间序列降噪应用Application of LMD and wavelet threshold in noise reduction of GNSS coordinate time series
邱小梦,陶国强,王奉伟,周世健
摘要(Abstract):
局部均值分解方法降噪过于粗糙,将认定为噪声的乘积函数(PF)分量直接剔除,导致有用信息丢失。为了有效提取GNSS站坐标时间序列的有用信息,该文提出一种局部均值分解和小波阈值相结合的降噪方法。通过局部均值分解将坐标时间序列分解为一系列PF分量和余项,依据消除趋势波动分析方法计算各PF分量的Hurst指数,利用小波阈值提取H≤1的PF分量中的有用信息,将提取出的信息与剩余PF分量叠加重构获得最终降噪的坐标时间序列。通过对5个测站的坐标时间序列进行实验,结果表明局部均值分解和小波阈值相结合的方法能够有效提取噪声分量中的有用信息,信噪比提高了27.8%,从而验证了该方法的有效性。
关键词(KeyWords): 局部均值分解;小波阈值;消除趋势波动分析;坐标时间序列;Hurst指数
基金项目(Foundation): 江西省教育厅科技项目(181523);; 东华理工大学长江学院院长基金项目
作者(Author): 邱小梦,陶国强,王奉伟,周世健
DOI: 10.16251/j.cnki.1009-2307.2021.08.005
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