一种新的自适应消噪方法

基于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办法。考虑到离散小波变换(DWT)不具有平移不变性,而静态小波变换(SWT)又不能很好地分析信号的高频部分,提出了一种新的自适应消噪方法。它根据CWT的提升方法,得到静态小波包的提升实现方法,并设计出适合本系统的确定最优小波包分解树的相应步骤,利用引入了更多动量因子的权系数迭代公式对各子带进行自适应匹配,并将匹配结果二次自适应,得到拟合的原信号。仿真中将其与其它两种基于小波的自适应方法进行了比较,表明该方法可在适当减小计算量的同时,进一步改善系统的滤波性能。

A New Method of Adaptive Noise

The method of adaptive denoising based on wavelet transform provides a feasible solution for radar signal filtering,seeing that the discrete wavelet transform(DWT) has not the characteristic of translation invariance of the wavelet coefficients,and the static wavelet transform(SWT) can not effectively analyze the high-frequency part of signals.This paper proposes a new adaptive denoising method.It educed the lifting method of static wavelet packet based on the lifting method of DWT,designed the corresponding steps of determining the optimal wavelet packet trees which is Suitable for this system,carried on adaptive matching to each sub-bands using the Weighting coefficient iterative formula which has more momentum factors.Finally,it took the second adaptive filter of the matching results to acquire the fitted signal.Compared with the other two adaptive methods based on wavelet transform,simulation results show that the method can further improve the filtering performance and properly decrease the calculation as well.