基于小波分析的脉冲星信号消噪处理

脉冲星信号是一种典型的非平稳信号,且信噪比非常小．目前对脉冲星信号的处理仅局限于对脉冲星信号不同周期的迭加．根据脉冲星信号的特点采用小波消噪的方法对其进行处理,并对小波的选取和分解层数的优化进行了研究．结果表明小波阈值消噪能够对脉冲星信号实现噪声剔除,达到既净化信号,又不丢失高频有用信息的目的．从而实现了迭加较少的信号周期就能够获得与较长时间迭加相似或更好的效果,可以大大提高脉冲星观测的轮廓精度．

Pulsar Signal Denoising Based on Wavelet Transformation

The pulsar signal is a kind of typical nonstationary random signal which SNR (Signal to Noise Ratio) is very low. The treatment to pulsar signal only confine to the adding of the pulsar signal by cycles at present. This paper carries on research to denoise the pulsar signal by using wavelet transformation, and choose the optimum wavelet and resolving level. The results indicate that denoising based on wavelet transformation not only highly improve the SNR, but also still hold high-frequency useful information. Thus only adding less signal cycles can get the similar or better precision of outline than long time observation.