卷积混叠盲信号分离的一种线性化方法

卷积混叠的盲信号分离是盲源分离问题中的难点．针对独立同分布的非高斯信号的卷积混叠，提出了一种新的盲解卷积方法——“两步提取法”：第一步消除所有源信号的延迟分量，提取仅含有源信号的线性混叠分量，使其转化为线性混叠盲源分离问题，称之为“卷积线性化”；第二步对“卷积线性化”后的估计信号进行分离，最终分离出源信号．同时，利用统计和矩阵理论，证明了设计“卷积线性化”滤波器的方法．仿真试验结果显示了该方法的可行性．

A Linearization Approach to Blind Separation of Convolution Mixture Signals

The blind separation of convolution mixture signals is a nodus in blind source separation. In this paper, aiming at the independently and identically distributed non-Gaussian signals, a novel approach to the blind deconvolution is presented, namely, the Two-Step Extraction. The first step is to eliminate the delay vectors of all sources and to extract only linear mixture signal vectors. Thus, the problem of convolution is transformed into the linear one. This step is called convolution linearization. The second step is to separate the estimated linearized signals and to obtain the source signals. Moreover, a method to design the filter of convolution linearization is proved by using the statistic and the matrix theories. The practicability of the proposed method is finally demonstrated by simulation.