离散不确定系统分布式鲁棒融合滤波器设计

针对一类离散多传感器动态模型的不确定系统，将鲁棒滤波理论与数据融合技术相结合，基于参数依赖Lyapunov函数，研究该离散系统的鲁棒融合滤波器设计问题。在集中式鲁棒融合滤波器的基础上，探讨了分布式加权融合滤波器的设计方法，通过仿真实验比较了鲁棒融合滤波器的性能。结果表明，利用该分布式加权融合算法，不仅对于解决当系统模型中存在参数不确定性时的滤波问题有较好的鲁棒性能和较低的计算量，而且在多传感器系统中对于满足不同精度鲁棒融合滤波器的设计需要具有较大的灵活性。

Design of distributed robust fusion filters for discrete uncertain systems

In terms of parameter-dependent Lyapunov function,the design problems of robust fusion filters for a class of discrete multi-sensor single dynamic model uncertain systems are dealt with combining the robust filter theory and data fusion technology.On the basis of the design method of the centralized robust fusion filter, distributed robust fusion filter is discussed.Moreover,the performance of this new filter for the multi-sensor dynamic systems is illustrated by the computer simulation.The results show that by using this distributed weight fusion method, it does not only have a better robust performance and lower computational complexity for resolving the filter problems when parameter uncertainties exist in the system model, but also have more flexibility to satisfy the design requirements of the robust fusion filters for multi-sensor systems with different precisions.