multisensor information fusion, measurement fusion, self-tuning fuser, white noise deconvolution, asymptotic global optimality Kalman filtering, convergence.," />
Journal of Systems Engineering and Electronics 2010, 21(4) 666-674 DOI:   10.3969/j.issn.1004-4132.2010.04.021  ISSN: 1004-4132 CN: 11-3018/N

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Keywords
multisensor information fusionzz')" href="#">

multisensor information fusion

measurement fusion
self-tuning fuser
white noise deconvolution
asymptotic global optimality Kalman filtering, convergence.
Authors
Xiaojun Sun and Zili Deng
PubMed
Article by Xiaojun Sun and Zili Deng

Self-tuning measurement fusion white noise deconvolution estimator with correlated noises

Xiaojun Sun and Zili Deng*

Department of Automation, Heilongjiang University, Harbin 150080, P. R. China

Abstract��

For the multisensor linear discrete time-invariant stochastic systems with correlated noises and unknown noise statistics, an on-line noise statistics estimator is presented by using the correlation method. Substituting it into the steady-state Riccati equation, the self-tuning Riccati equation is obtained. 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 fusion white noise deconvolution estimator converges to the optimal fusion steadystate white noise deconvolution estimator in a realization, so that it has the asymptotic global optimality. A simulation example for Bernoulli-Gaussian input white noise shows its effectiveness.

Keywords�� multisensor information fusionzz')" href="#">

multisensor information fusion   measurement fusion   self-tuning fuser   white noise deconvolution   asymptotic global optimality Kalman filtering, convergence.  

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DOI: 10.3969/j.issn.1004-4132.2010.04.021
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