DocumentCode :
2849594
Title :
Self-tuning white noise deconvolution fuser with asymptotic global optimality
Author :
Sun, Xiaojun ; Deng, Zili
Author_Institution :
Dept. of Autom., Heilongjiang Univ., Harbin, China
fYear :
2010
fDate :
26-28 May 2010
Firstpage :
601
Lastpage :
606
Abstract :
White noise deconvolution or input white noise estimation has a wide range of applications including oil seismic exploration, communication, signal processing, and state estimation. For the multisensor linear discrete time-invariant stochastic systems with correlated noises and unknown noise statistics, an on-line noise statistics estimator is given by the correlation method. Using the Kalman filtering method, based on the self-tuning Riccati equation, a self-tuning weighted measurement fusion white noise deconvolution estimator is presented. By the dynamic error system analysis (DESA) method, it is proved that the self-tuning white noise deconvolution fuser converges to the steady-state optimal white noise deconvolution fuser in a realization so that it has the asymptotic global optimality. A simulation example for a 3-sensor system with Bernoulli-Gaussian input white noise shows its effectiveness.
Keywords :
Kalman filters; Riccati equations; correlation methods; deconvolution; optimal systems; state estimation; stochastic systems; Bernoulli-Gaussian input white noise; Kalman filtering; asymptotic global optimality; correlation method; dynamic error system analysis; input white noise estimation; multisensor linear discrete time-invariant stochastic system; oil seismic exploration; online noise statistics estimator; self-tuning Riccati equation; self-tuning weighted measurement fusion white noise deconvolution estimator; self-tuning white noise deconvolution fuser; signal processing; state estimation; steady-state optimal white noise deconvolution fuser; Correlation; Deconvolution; Kalman filters; Petroleum; Riccati equations; Signal processing; State estimation; Statistics; Stochastic systems; White noise; Convergence; Global Optimality; Kalman Filtering; Multisensor Information Fusion; Self-tuning Fuser; Weighted Measurement Fusion; White Noise Deconvolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
Type :
conf
DOI :
10.1109/CCDC.2010.5498963
Filename :
5498963
Link To Document :
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