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Self-tuning decoupled fusion Kalman filter based on the Riccati equation
Authors:Xiaojun SUN  Peng ZHANG  Zili DENG
Affiliation:(1) Department of Automation, Heilongjiang University, Harbin, 150080, China
Abstract:An online noise variance estimator for multisensor systems with unknown noise variances is proposed by using the correlationmethod. Based on the Riccati equation and optimal fusion rule weighted by scalars for state components, a self-tuning component decoupled information fusion Kalman filter is presented. It is proved that the filter converges to the optimal fusion Kalman filter in a realization by dynamic error system analysis method, so that it has asymptotic optimality. Its effectiveness is demonstrated by simulation for a tracking system with 3 sensors. __________ Translated from Control and Decision, 2008, 23(2): 195–199 译自: 控制与决策]
Keywords:multi-sensor information fusion  decoupled fusion  self-tuning fuser  Kalman filter  convergence in a realization
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