基于提升静态小波变换的自适应消噪方法

基于离散小波变换的自适应消噪方法为雷达信号的滤波提供了一种可行的方法.但DWT不具有平移不变性,若不用相同的小波对滤波后的信号进行重构,则会带来较大的重构误差.针对这一现象,提出了基于提升静态小波变换的自适应消噪方法,它首先根据DWT的提升方法,得到SWT的提升和对偶提升实现方法,然后通过SWT的提升方法将信号分解为多个子带,利用引入更多动量因子的权系数的迭代公式进行自适应匹配.并对匹配结果二次自适应,得到拟合的原信号.仿真结果表明,该方法可在计算量增加不大的前提下,进一步改善系统的滤波性能.

Denoising method based on lifting static wavelet transforms

The method of adaptive denoising based on discrete wavelet transform (DWT) provides a feasible solution for radar signal filtering,but DWT has not the characteristic of translation invariance of the wavelet coefficients.If the signal reconstruction is not with the same wavelet,it will bring greater reconstruction error.Aiming at this phenomenon,an adaptive denoising method based on the lifting static wavelet transform(SWT) is proposed.Firstly,the lifting and dual lifting method of SWT based on the lifting method of DWT are educed.Then the signal is decomposed as multisub-bands by lifting SWT,and adaptive match is made by using the weights coefficients iterative formula which has more momentum factors.Finally,the second adaptive filter of the matched results is taken to acquire the fitted signal.Simulation results show that the method can further improve the filtering performance if there is not a much increase in the calculation amount.