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 functions 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“db6”and“sym4”soft threshold de-noising methods, the proposed algorithm can achieve higher SNR while keeping more useful details of Pulsar signal.