带白色公共干扰噪声的反卷积系统的多传感器信息融合估计算法  

Multi-sensor Information Fusion Estimation Algorithm for Deconvolution System with White Common Disturbance Noises

作　　者：李恒[1] 王浩[1] 韩波[1] 李怀敏[1] 李净达[1] 

机构地区：[1]阜阳师范学院计算机与信息工程学院,安徽阜阳236037

出　　处：《河北科技师范学院学报》2016年第1期52-56,共5页Journal of Hebei Normal University of Science & Technology

基　　金：国家自然科学基金资助项目(项目编号:No.61401101);阜阳师范学院自然科学项目(项目编号:2015FSKJ09;2015FSKJ10;2016FSKJ16)

摘　　要：对于一个带未知的白色公共干扰噪声的反卷积系统,在部分参数未知的前提下,提出一种基于自回归滑动平均模型的多传感器信息融合估计算法。使用该算法可首先得到对于自回归参数的无偏融合估计,然后可得到对于公共干扰噪声的噪声统计特性的无偏融合估计,最后证明了估计的收敛性。该算法可用于石油勘探领域的背景噪声预估计。用一个Matlab仿真例子对算法的有效性做了说明。When the parameters were partly unknown,a multi-sensor multi-stage information fusion estimation algorithm based on the autoregressive moving average innovation model was proposed for the deconvolution system with unknown white common disturbance noises. By the aid of the algorithm,the unbiased fused estimations of the autoregressive parameters could be obtained firstly,then the unbiased fused estimations of the common disturbance noise statistics and finally the convergence of the estimations. This algorithm could be applied to estimate predictively the background noises in the field of petroleum exploration. An example was taken to display the effectiveness of the algorithm.

关 键 词：白色公共干扰噪声 反卷积系统 自回归滑动平均模型 多传感器信息融合 估计算法 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]