在实际的计算机系统中,当观测数据通过网络被传送到远程控制器时,时常发生具有随机性的时滞或观测数据丢失现象。针对这一问题,研究了数据传输具有一步随机延迟的多传感器动态系统的融合估计问题。按照标量加权的线性最小方差信息融合准则,对基于每个单传感器得到的局部最优状态估计进行了融合,得到了全局最优状态估计。最后,给出了仿真例子,证实融合估计的效果在精度上优于基于每个单传感器的估计。
Sensor delay and observation uncertainty often occur in practical computer systems, e. g. , when the measurement is transmitted to a remote controller through a network medium. Multi-sensor fusion estimation weighted by scalars with one-step random sensory delay was studied. According to information fusion criterion weighted by scalars in the linear minimum variance sense, a global optimal state estimator was obtained via fusion of local optimal state estimates for each single sensor subsystem. A simulation example is given to show that the precision of the fusion estimation is superior to that based on each single sensor subsystem.