Title :
Multisensor optimal information fusion white noise deconvolution filter
Author :
Wang Xin ; Zhu Qidan ; Wu Yebin
Author_Institution :
Dept. of Autom., Harbin Eng. Univ., Harbin, China
Abstract :
Using the modern time series analysis method and white noise estimation theory, under the linear minimal variance optimal information fusion criterion, a multisensor information fusion white noise deconvolution filter is presented for systems with correlated noises. The formula of computing covariances among filtering errors of sensors is presented, which can be applied to compute the optimal fused weighting matrices. 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.
Keywords :
Gaussian noise; deconvolution; filtering theory; sensor fusion; time series; white noise; Bernoulli-Gaussian white noise deconvolution filter; filtering errors; multisensor optimal information fusion; oil seismic exploration; optimal fused weighting matrices; signal processing; time series analysis method; white noise estimation theory; Analysis of variance; Deconvolution; Estimation theory; Information analysis; Information filtering; Information filters; Lubricating oils; Sensor fusion; Time series analysis; White noise; correlated noises; deconvolution; optimal information fusion; reflection seismology; white noise estimators;
Conference_Titel :
Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-2692-8
Electronic_ISBN :
978-1-4244-2693-5
DOI :
10.1109/ICMA.2009.5245986