基于小波域模糊阈值算法的脉冲星微弱信号消噪

脉冲星辐射信号具有极低的信噪比,传统降噪算法难以在抑制噪声的同时保留细节信息。为此,提出一种模糊阈值小波降噪算法。该算法通过引入模糊理论,建立隶属度函数,计算信号每个采样点的隶属度,再利用小波阈值消噪算法设定门限,将隶属度大于门限的采样值划归为信号,反之为噪声,从而达到降噪的目的。实验结果表明:与小波"db6"和小波"sym4"软阈值消澡算法相比,该算法能有效提高脉冲星辐射信号的信噪比,能保留较多的有用细节信息,避免脉冲累积轮廓过于光滑。

Pulsar Weak Signal De-noising Based on Wavelet Fuzzy Threshold Algorithm

Pulsar signal has very low signal to noise ratio and the traditional de-noising algorithm is difficult to suppress the noise while preserving the details. Thus, a Wavelet Fuzzy Threshold de-noising algorithm is proposed. Firstly, the membership fimctions are set up by introducing the fuzzy theory in the algorithm, the membership grade of each sample is calculated. And then the threshold is set up by using the wavelet threshold de-noising methods, the samples which are larger than the threshold are categorized to the signal, the others to the noise so as to achieve the aim for suppressing the noise and retaining the useful signal. Finally, the experiment results show that, compared to wavelet＂dbr＂and＂sym4＂soft threshold de-noising methods, the proposed algorithm can achieve higher SNR while keeping more useful details of Pulsar signal.