The application of wavelet transformation in pulsar signal denoising

Pulsar signal is a non-stationary signal, its signal to noise ratio (SNR) is extremely low. As for the noise contaminated signal in pulsar observation, the contaminated pulsar signal characteristics were analyzed in this paper. The pulsar signal was deniosed by wavelet transform according to the frequency characteristics of pulsar signal and noise. The basic wavelet selection, wavelet decomposition scale determination and threshold selection were also studied in this paper. The results show that the wavelet transform denoising algorithm can effectively eliminate the noise of pulsar signal, and improve its signal to noise ratio, while preserving the signal details. After wavelet transformation denoising, a better result can be achieved at lower Superposition of observation periods.