DocumentCode
3358765
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
fYear
2009
fDate
9-12 Aug. 2009
Firstpage
2447
Lastpage
2451
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICMA.2009.5245986
Filename
5245986
Link To Document