改进局部均值分解在变形监测数据处理中的应用

Application of Improved Local Mean Decomposition in Deformation Monitoring Data Processing

针对单一的局部均值分解(LMD)方法在信号去噪中的缺陷,在LMD方法的基础上引入奇异谱分析(SSA)方法,构建新的LMD-SSA组合去噪方法。该组合去噪方法实现去噪的步骤为:首先,使用LMD方法将信号分解为若干个乘积函数(PF),并根据连续均方误差确定高频PF分量与低频PF分量分界点;其次,使用SSA方法对高频PF分量进一步处理,提取高频PF分量中的有用信息;最后,重构高频PF分量中有用信息与低频PF分量得到最终去噪后信号。为检验本文提出的组合去噪方法的有效性与优越性,使用仿真信号与实测全球导航卫星系统(GNSS)信号进行去噪实验,结果表明本文提出组合去噪方法较单一的LMD方法、SSA方法去噪效果更好,能够准确提取原始信号中真实的变形信息。

Aiming at the defects of single local mean decomposition(LMD)method in signal denoising,this paper introduces singular spectrum analysis(SSA)method on the basis of LMD method,and constructs a new LMD-SSA combined denoising method.The steps of the combined denoising method are as follows:first,the signal is decomposed into several product functions(PF)using LMD method,and the dividing point of high-frequency PF component and low-frequency PF component is determined according to the continuous mean square error;secondly,the SSA method is used to further process the high-frequency PF component and extract the useful information in the high-frequency PF component;finally,the useful information in the high-frequency PF component and the low-frequency PF component are reconstructed to obtain the final denoised signal.In order to test the effectiveness and superiority of the combined denoising method proposed in this paper,the simulated signal and the measured global navigation satellite system(GNSS)signal are used for denoising experiments.The results show that the combined denoising method proposed in this paper has better denoising effect than the single LMD method and SSA method and can accurately extract the real deformation information in the original signal.