基于VMD与SSA的OTDR信号去噪算法

为对光时域反射计(Optical Time Domain Reflectometer, OTDR)数据进行去噪处理，提出了一种基于变分模态分解(Variational Mode Decomposition, VMD)与奇异谱分析(Singular Spectrum Analysis, SSA)的去噪算法。首先，对OTDR数据进行VMD分解；然后根据相关系数准则判定有效分量，并采用SSA对与原信号相关系数较小的分量进行处理；再对所有分量求和，得到重构后的信号，从而实现数据信噪比的提高。经实验验证，该算法的去噪效果良好，容易实现，具有较大的实用价值。

OTDR Signal Denoising Algorithm Based on VMD and SSA

To denoise the optical time domain reflectometer (OTDR) data, a denoising algorithm based on variational mode decomposition (VMD) and singular spectrum analysis (SSA) is proposed. First, perform VMD decomposition on the OTDR data; then, determine the effective component according to the correlation coefficient criterion, perform singular spectrum analysis on the component with the smaller correlation coefficient to the original signal, and then sum all the components to obtain the reconstructed signal. So signal-to-noise ratio of the data is improved. It is verified by experiments that the algorithm has good denoising effect, simple implementation and great application value.