Self-tuning measurement fusion white noise deconvolution estimator with correlated noises |
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Authors: | Xiaojun Sun Zili Deng |
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Institution: | Department of Automation,Heilongjiang University,Harbin 150080,P.R.China |
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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. |
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Keywords: | multisensor information fusion measurement fusion self-tuning fuser white noise deconvolution asymptotic global optimality Kalman filtering convergence |
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