多传感器最优信息融合白噪声反卷积滤波器

Multisensor optimal information fusion white noise deconvolution filter

中文关键词  最优加权融合  分布式融合  反射地震学  白噪声反卷积估值器  Wiener滤波器

英文关键词  optimal weighted fusion  distributed fusion  reflection seismology  white noise deconvolution estimators  Wiener filter

中文摘要

      应用现代时间序列分析方法和白噪声估计理论,基于线性最小方差意义下按标量加权最优信息融合准则,对于带白色和有色观测噪声的多传感器单通道系统,提出了分布式融合白噪声反卷积滤波器.它由局部白噪声反卷积滤波器加权构成.可统一处理融合滤波、平滑和预报问题.给出了计算局部滤波误差互协方差公式,可用于计算最优加权.同单传感器情形相比,可提高融合滤波器精度.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白噪声反卷积滤波器的仿真例子说明了其有效性.

英文摘要

      Using the modern time series analysis method and white noise estimation theory and based on the linear minimum variance optimal information fusion criterion weighted by scalars,a distributed fusion white noise deconvolution filter is presented for multisensor single channel systems with white and colored measurement noises.The proposed filter consists of weighting local white noise deconvolution filters,which can handle the fused filtering,smoothing,and prediction problems in a unified framework.The formula for computing the cross-covariances among local filtering errors is also given,which is applied to compute the optimal weights.Compared with the single sensor case,the accuracy of the fused filter is improved.It can be applied to signal processing in oil seismic exploration.Finally,a simulation example for information fusion Bernoulli-Gaussian white noise deconvolution filter with three-sensor shows its effectiveness.