Multisensor information fusion white noise estimator

被引：0

作者：

Wang, Xin ^{[1
]}

Li, Yun ^{[1
]}

Deng, Zili ^{[1
]}

机构：

[1] Heilongjiang Univ, Dept Automat, Harbin 150080, Peoples R China

来源：

WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年

关键词：

multisensor information fusion; optimal weighting fusion; reflection seismology; deconvolution; white noise estimators; Wiener filter;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Using the modern time series analysis method and white noise estimation theory, under the linear minimum variance optimal information fusion criterion, for multisensor systems with colored measurement noise, the multisensor optimal information fusion white noise deconvolution Wiener filter is presented, which consists of weighting local white noise deconvolution Wiener filters. The formula of computing covariances among the local filtering errors is presented, and the formula of optimal weighting coefficients is also given. 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. A simulation example for information fusion Bernoulli-Gaussian white noise deconvolution filter shows its effectiveness.

引用

页码：1492 / +

页数：2