基于Laplace分布的非下采样小波包脉冲星信号消噪

为了提高脉冲星信号的去噪效果,提出了一种基 于非下采样小波包(NWP)分解的局部Laplace模型消噪方法。 首先对真实脉冲星信号进行NWP分解,统计真实脉冲星信号NWP系数的分布特性, 建立真实脉冲星信号小波包系数的Laplace分布模型；然后在Laplace先验概率分布的基础 上,根据最大后 验概率(MAP)估计准则,利用含噪脉冲星信号的小波包系数对真实脉冲星信号的小波包系数 进行有效估算；最后 对估算出的小波包系数进行NWP重构,得到消噪后的脉冲星信号。采用不同 的脉冲星信号进行实 验分析的结果表明,与经典的基于高斯分布的非下采样小波(NSW)消噪和NWP消噪相比,本文 方法可以 更有效地去除噪声,同时更好地保留信号中的微脉冲等细节信息,在信噪比(SNR)、均方根误差(RMSE)、相关系数(CC)和峰值相对误差(REPV)等都 有较好的改善。

Pulsar signal denoising method based on Laplace distribution in nosubsampled wavelet packet domain

To improve the denoising effect of pulsar signal,a new method is proposed in und ecimated wavelet packet domain based on local Laplace prior model.First,the undecimated wavelet packet coefficient s distribution characteristics of the true noise-free pulsar signal are counted,and the Laplace probability den sity function model of the true signal wavelet packet coefficients is established.Then,the denosied wavelet packet coe fficients are estimated by using the noisy pulsar wavelet coefficients based on maximum a posteriori (MAP) criterion.Finally,the denoised pulsar signal is obtained by nosubsampled wavelet packet reconstruction of the estimated coefficients.The experimental results show that the proposed method can get better denosing effect than the nosubsampled wavelet met hod and the nosubsampled wavelet packet method based on Gaussian distribution,which can more better remove the n oise of pulsar signal and more effectively preserve the micro-pulse detail information.Moreover,the propos ed method has a better improvement in signal-to-noie (SNR),root mean square e rror,correlation coefficient and peak relative error,etc.