多传感器信息融合白噪声去卷Wiener滤波器和平滑器  

Multi-sensor information fusion white noise de-convolution Wiener filter and smoother

作　　者：李云[1] 王欣[1] 邓自立[1] 

机构地区：[1]黑龙江大学电子工程学院,黑龙江哈尔滨150080

出　　处：《黑龙江大学自然科学学报》2006年第2期231-234,共4页Journal of Natural Science of Heilongjiang University

基　　金：国家自然科学基金资助项目(60374026)

摘　　要：应用现代时间序列分析方法和白噪声估计理论,在线性最小方差最优信息融合准则下,提出了多传感器最优信息融合白噪声去卷W iener滤波器和平滑器,其中给出了局部滤波误差之间的协方差公式,它可被用于计算最优融合加权系数.同单传感器情形相比,可提高融合估值器精度.它可应用于石油地震勘探信号处理.一个3传感器信息融合Bernoulli-Gaussian白噪声去卷滤波器的仿真例子说明了其有效性.Using the modern time series analysis method and white noise estimation theory, under the linear minimum variance optimal information fusion criterion, the multi - sensor optimal information fusion white noise de - convolution Wiener filter is presented. Compared with the single sensor case ,the accuracy of the fused estimators is improved. It can be applied to signal processing in oil seismic exploration. A simulation example for 3 - sensor infor- mation fusion Bernoulli - Gaussian white noise de - convolution filter shows their effectiveness.

关 键 词：最优信息融合 反射地震学 反卷积 白噪声估值器 WIENER滤波器 

分 类 号：O211.64[理学—概率论与数理统计]