脉冲星信号的模糊阈值小波降噪算法

为了提高脉冲星辐射脉冲信号的信噪比,提出了基于模糊阈值的小波降噪算法.该算法的核心思想为:引入模糊理论,通过建立隶属度函数,计算出每个采样点信号幅值的隶属度,再利用小波阈值消噪的方法设定门限来分析隶属度,将隶属度大于门限的采样值划归为信号,反之为噪声,从而达到压抑噪声、保留信号的目的.实验结果表明,与基于极大极小原理和Stein无偏似然原理的降噪方法相比,基于模糊阈值的小波降噪算法将脉冲信号的信噪比提高了大约5~6 dB,同时可以保留信号的细节.新算法为脉冲星信号处理与应用提供了一个行之有效的算法.

Wavelet Denoising Algorithm Based on Fuzzy Threshold for Pulsar Signal

In order to improve the signal-to-noise ratio(SNR) of the pulsar signal,a wavelet denoising algorithm based on fuzzy threshold is put forward.The core of the algorithm is as follows: firstly,the fuzzy theory is introduced,by formulating the membership functions, the membership grade of each sample is calculated,then the threshold is set up and the membership grade is analyzed by using the wavelet denoising method,the samples that are larger than the threshold are categorized to the signal,and the others to the noise so as to achieve the aim for suppressing the noise and retaining the signal.Simulation result shows that,compared to the two methods based on minimax theory and stein unbias similar estimate theory respectively,the SNR of the pulsar signal of the proposed algorithm is increased by 5 to 6 dB while keeping the details of it.