Self-tuning decoupled fusion Kalman filter based on the Riccati equation
Self-tuning decoupled fusion Kalman filter based on the Riccati equation作者机构：Department of AutomationHeilongjiang UniversityHarbin 150080China
出 版 物：《Frontiers of Electrical and Electronic Engineering in China》 (中国电气与电子工程前沿（英文版）)
年 卷 期：2008年第3卷第4期
页 面：459-464页
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
基 金：supported by the National Natural Science Foundation of China(Grant No.60374026) the Science and Technology Research Foundation of Heilongjiang Education Department(11523037),Automation Control Key Laboratory of Heilongjiang University
主 题：multi-sensor information fusion decoupled fusion self-tuning fuser Kalman filter convergence in a realization
摘 要：An online noise variance estimator for multi-sensor systems with unknown noise variances is proposed by using the correlation *** on the Riccati equa-tion and optimal fusion rule weighted by scalars for state components,a self-tuning component decoupled informa-tion fusion Kalman filter is *** 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 *** effectiveness is demon-strated by simulation for a tracking system with 3 sensors.
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