摘要
提出一种新的标量加权多传感器线性最小方差意义下的最优信息融合准则.该准则考虑了局部估计误差之间的相关性,只需计算加权标量系数,避免了加权矩阵的计算,明显减小了计算量,便于实时应用.运用稳态Kalman滤波理论,基于该融合准则,给出了多传感器最优信息融合稳态Kalman滤波器.在所有局部滤波器达到稳态时,只需一次融合便可获得信息融合稳态滤波器,算法简单.仿真例子验证了其有效性.
A new multi-sensor optimal information fusion criterion weighted by scalars is presented in the linear minimum variance sense. The criterion considers the correlation among local estimate errors, and only computing the weighted scalar coefficients is needed. Therefore the computational burden can obviously be reduced, and it is convenient to apply in real time. Using steady-state Kalman filtering theory, a multi-sensor optimal information fusion steady-state Kalman filter is given based on this fusion criterion. The information fusion steady-state filter can be obtained only by one time fusing after all local filters enter steady states. Simulation example shows the effectiveness of the proposed method.
出处
《控制与决策》
EI
CSCD
北大核心
2004年第2期208-211,共4页
Control and Decision
基金
国防基础科研资助项目.
