基于经验小波变换的地震动信号分离方法

Seismic signal separation method based on EWT

地面目标运动时激励的地震动信号可用于目标定位和识别。而当存在多种地面目标时,震动信号将发生混叠,不利于信号分析。经验小波算法根据信号频谱极大值点可将频谱分割为多个区间,并在各区间构造正交小波函数对信号进行变换,获得多个经验模态信号。地震动信号的频谱峰值过于密集,若单纯根据峰值分割区间则容易将同种信号分解为多个模态,造成模态数量过多,影响信号分析效果。为解决该问题,在信号频谱基础上通过多次提取包络线,减少频谱峰值;再根据地震动信号特征,提出频谱阈值分割法,增强不同频率信号的区分度。实验表明,改进EWT算法对不同目标产生的地震动信号具有较好的分离效果。

Seismic signals generated by ground target movement can be used for target location and recognition.When there exist multiple types of ground targets,the signal aliasing phenomenon may interfere signal analysis.EWT algorithm divides the spectrum into several segments according to its maxima value,and transform the signals by constructing orthogonal wavelet functions in each segment to obtain multiple empirical mode signals.However,if the segments are merely devided according to the maxima value,dense peaks may result in too many modes.To solve this problem,spectrum envelope is extracted repeatedly to reduce the number of peaks,and then spectral threshold segmentation algorithm is proposed to enhance discrimination among different signals.Experiments show that improved EWT algorithm has better separation effect for seismic signals from different targets.