利用经验模态分解的高频水声信号滤波方法  

A filtering method for high frequency underwater acoustic signal using a improved empirical mode decomposition

作　　者：丁浩[1] 赵建昕[1] 笪良龙[1] 

机构地区：[1]海军潜艇学院,青岛266000

出　　处：《应用声学》2016年第4期316-323,共8页Journal of Applied Acoustics

基　　金：总装预言基金项目(9140A03060213JB15039)

摘　　要：研究了一种高频水声信号的滤波问题,提出了一种改进的经验模态分解加小波阈值滤波方法。首先对信号进行带通滤波处理,再进行经验模态分解,将分解得到的各个模态转换为频域信号,采用小波软阈值方法对这些频域信号进行滤波,最后对信号进行重构,并转换为时域信号。经数值仿真与试验数据验证表明此方法是可行有效的,与原基于经验模态分解的小波阈值滤波方法相比,本方法滤波效果较好:对不同输入信噪比的仿真信号进行滤波后,本方法的输出信噪比最大提高17.41 d B,滤波后所得信号与加噪前纯信号的相关系数最大提高0.90;对实验数据进行滤波后,不同时间段信号的相关系数最大提高0.62。The purpose of this work is to study a method for filtering high frequency underwater acoustic signals based on the ensemble empirical mode decomposition （EEMD） and the wavelet soft threshold （WST） methods. Firstly, the band-pass filter is used to denoise the signal with noise. Secondly, the EEMD method is used to process the signal, then the intrinsic mode functions （IMFs） are transformed to signals in the frequency domain, respectively. Thirdly, the signals in the frequency domain are filtered by using the WST method. Finally, the IMFs are added to reconstruct the signal in the frequency domain, and then the signal in the time domain is obtained. The given method is proved to be feasibly and effectively by numerical simulations and experiment data. Compared with the existing filter method, the following acquaintances can be observed. （1） There is 17.41 dB output signal noise ratio （SNR） improved at most for simulation signal under different input SNRs, respectively. （2） The correlative coefficient between the signal filtered and the simulation signal without noise can be improved 0.90 at most. （3） The correlative coefficient between different periods of time for experiment data can also be improved 0.62 at most.

关 键 词：经验模态分解 小波软阈值 高频信号 滤波 水声 

分 类 号：TN911[电子电信—通信与信息系统]