基于SαSG分布噪声模型的自适应混合矩滤波方法

Adaptive mixed norm filtering algorithm based on SαSG noise model

α-稳定分布可以更好地描述实际应用中所遇到的具有显著脉冲特性的随机信号和噪声。与其他统计模型不同,α-稳定分布没有统一闭式的概率密度函数,其二阶及二阶以上统计量均不存在。针对系统中存在独立SαS噪声与高斯噪声,基于SαSG分布模型,提出了一种稳定分布与高斯混合噪声环境下的自适应混合矩滤波的修正RMN(混合参数)算法,并对算法进行了步长归一化改进。计算机模拟和分析表明,这种算法是一种在SαSG分布背景噪声条件下具有良好韧性的滤波方法。

Alpha-stable distribution, a generalization of Gaussian, was better for modeling impulsive noises than Gaussian distribution in signal processing. This class of process had no close form of probability density function and finite second order moment. A new adaptive mixed moments filtering algorithm based on SαSG noise model was proposed. The simulation experiments show that the proposed new algorithm is more robust than the conventional algorithm.