研究了异质传感器对参数矢量进行的测量，测量数据基于线性均方估计的最优融合算法。提出和证明了异质传感器数据的最优线性融合定理，并得出“精度再差的传感器参与数据融合后都有利于提高系统的测量精度”这一结论。

By introducing information fusion techniques into optimal preview control, a new theory of Information Fusion Optimal Preview Control (IFOPC) for nonlinear discrete system is proposed in this paper. All information on control system which includes ideal control strategy, expected objective trajectory and dynamics of system, is regarded as measure information of control system. Therefore, the problem of optimal control can be transferred into the problem of information fusion estimate. It should be pointed out that the IFOPC consists of optimal co-state generator and optimal regulator, in which the optimal co-state generator is just a extended Kalman filter. Firstly, the information fusion estimate theorems are described in brief. Secondly, an algorithm of IFOPC is deduced in detail. Thirdly, some key techniques of IFOPC are discussed, which include the selection of preview step number and the determination of Kalman filter initial values. Finally, the validity of the proposed control strategy is confirmed by the simulation of manipulator shift control. The simulation results show good tracking performance of the IFOPC based nonlinear system.

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研究了不同模型下的推广联合滤波算法。基于信息融合理论和信息守恒原理，提出信息分配是信息融合的逆过程的观点，给出和证明了信息分配定理，为推广联合滤波算法提供了理论基础。以某卫星组合姿态确定系统为例，详细讨论了推广联合滤波的结构及其实现过程。理论分析和数学仿真结果表明:推广联合滤波算法比现有的联合滤波算法计算量小，且推广联合滤波算法能够同时保证全局最优和局部最优，而现有的联合滤波算法不是局部最优。