针对淹没在1/f分形噪声中的有用信号恢复问题,提出了一种基于小波变换与Kalman滤波的多尺度滤波算法.首先将带有1/f分形噪声的信号分解成多尺度的子带信号,通过小波变换对1/f分形噪声的白化作用,消除了1/f分形噪声的自相似性和长程相关性.然后在小波域内,利用Kalman滤波实现了噪声和有用信号的分离,估计出了各子带中的有用信号.最后进行小波重构,较好地恢复出淹没在1/f分形噪声中的有用信号.仿真实验表明,使用多尺度Kalman滤波器能有效地抑制分形噪声,显著地提高了信噪比.
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