脉冲噪声下基于共变序列的自适应时延估计  

Adaptive time delay estimation based on covariation series in impulsive noise

作　　者：刘文红[1,2] 汪源源[1] 王斌[1] 

机构地区：[1]复旦大学电子工程系,上海200433 [2]上海电机学院电子信息学院,上海200240

出　　处：《系统工程与电子技术》2009年第8期1781-1784,共4页Systems Engineering and Electronics

基　　金：国家基础研究项目(2006CB705707);国家自然科学基金(30570488);中国博士后科学基金(20070420602);上海市重点学科项目(B112)资助课题

摘　　要：针对实际应用中常遇到的脉冲性噪声问题,以α稳定分布模型进行描述,提出了一种基于共变序列的自适应时延估计方法,简称CAED。该方法通过求取两个观测序列的互共变和一个观测序列的自共变,去除了不相关脉冲噪声,保留了观测序列间时间延迟的信息;将自共变、互共变序列作为两个自适应滤波器的输入信号,在最小均方误差准则控制下,由收敛的两个滤波器权系数矢量峰值位置之差可获得源信号到达两个接收端的相对时延。通过计算机仿真对比实验验证了该算法在强脉冲噪声、低信噪比情况下的优良估计性能。A novel adaptive time delay estimation approach, referred to as CAED for short, is proposed based on covariation series because the impulsive noise may usually be modeled as a-stable distribution in the ap plication. Firstly, the impulsive noise is removed and the mixed signal-to noise ratio （MSNR） is improved by computing the cross-covariation between two received signals and the auto-covariation of one received signal with the information of the time delay still remaining. Secondly, the cross-covariation and auto-covariation series are regarded as time series and are put into two adaptive filters. The difference between the peak locations of two filter weight coefficients indicates the relative time delay between two received signals when they are convergent under the least mean square error criterion. Computer simulation studies show that the CAED algorithm gives an improved approach to estimating the time delay with a stable noises under the lower MSNR.

关 键 词：信号与信息处理 时延估计 共变 脉冲噪声 Α稳定分布 自适应滤波器 

分 类 号：TN911.7[电子电信—通信与信息系统]