关键词: 自动控制技术, 信息融合, 最优估计, 随机动态系统, 卡尔曼滤波

Abstract: The filtering methods based on information fusion estimation in linear or nonlinear systems was presented for the filtering problem in discrete dynamic stochastic system. For linear filtering, one step predictive information and state measurement information are used to obtain the optimal fusion estimate of the system state, and the uniformity between linear filtering and standard Kalman filtering was proved. Based on the nonlinear information fusion theorem, an iterative fusion estimation method with small computation cost was derived. Furthermore, a solution to the selection of initial filtering values was investigated.

Key words: automatic control technology, information fusion, optimal estimation, dynamic stochastic system, Kalman filtering