摘要
近年来,单通道盲分离作为信号处理领域中的重要分支,受到了人们越来越多的关注。粒子滤波和进化算法都是利用一群粒子(个体)进行逼近估计的方法,同时各有各的优势。本文将粒子滤波与进化算法两种方法结合起来,既利用了粒子滤波估计的准确性,又利用了进化算法对收敛性进行保证,提出了一种解决单通道盲分离问题的新方法。文中针对两路同频BPSK混合信号,采用粒子滤波的架构,同时利用赌轮选择方法对粒子进行重要性采样,最后根据最大后验估计的方法对当前时刻的粒子对进行估计。
As an important branch of signal processing, single channel blind separation has received more and more attention in recent years. Particle filtering and evolutionary algorithm can both use a population of particles approximate optimal solutions sets, and each method has its own advantages. In this paper, combining the two methods, we proposed an algorithm for single channel blind separation. Not only does it exploit the accuracy of the particle filtering, but it takes advantage of the good convergence of the evolutionary algorithm. For co-frequency signals, we used the frame of particle filtering, do important sampling with roulette wheel selection, and estimate current state by Maximum Likelihood sequences estimation（MLSE）.
出处
《计算机科学》
CSCD
北大核心
2013年第06A期61-63,共3页
Computer Science
基金
国家自然科学基金(60872041
61072066)资助
关键词
单通道盲分离
粒子滤波
进化算法
Single-channel blind separation,Particle filtering,Evolutionary algorithm
