基于EMD-R/S分析的太赫兹光谱降噪

针对太赫兹时域光谱系统由于延时线的重合抖动、采样抖动等产生的噪声,提出使用经验模态分解-R/S分析方法对太赫兹光谱信号进行降噪。采集太赫兹时域光谱系统的时域信号,根据EMD算法将信号分解成本征模态函数(IMF);使用R/S分析法分别计算各个IMF的Hurst指数。根据设定的阈值判断是否各个IMF是否存在均值回复的情况。如果IMF存在均值回复的现象,则使用原始信号与IMF信号作差,所得信号即为降噪后的时域信号。实验结果表明,与小波降噪算法相比,EMD-R/S分析算法能够有效地对太赫兹时域光谱信号降噪,能够有效还原太赫兹光谱信号特征。

TERAHERTZ SINGAL DENOISING METHOD BASED ON EMD-R/S ANALYSIS

In the terahertz time-domain spectroscopy system,due to the coincidence jitter of the delay line and the noise generated by sampling jitter,the empirical mode decomposition-R/S analysis method is proposed to denoise the terahertz spectral signal.The time domain signal of the terahertz time-domain spectroscopy system was acquired,and the signal was decomposed into a series of intrinsic mode components(IMF)according to the EMD algorithm.The Hurst index of each IMF was calculated using R/S analysis.It was determined whether the respective IMFs had an average reply according to the set threshold.If the IMF had the phenomenon of mean recovery,the original signal was used to make a difference with the IMF signal,and the resulting signal was the time domain signal after noise reduction.The experimental results show that compared with the wavelet denoising algorithm,the EMD-R/S analysis algorithm can effectively denoise the terahertz time-domain spectral signal and effectively reduce the terahertz spectral signal characteristics.