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研究带多传感器和相关观测噪声的离散随机奇异系统的分布式融合状态估计问题.核心思想是将带多传感器的随机奇异系统转化为一个等价的非奇异系统组.在得到局部非奇异系统的状态估计后,利用线性最小方差意义下的最优加权融合算法,得到原系统的全阶最优融合滤波器和平滑器.仿真算例表明,融合估值器优于每个局部估值器.
The problem of distributed fusion state estimation for discrete stochastic singular systems with multiple sensors and correlated observation noise is studied.The core idea is to transform a stochastic singular system with multiple sensors into an equivalent nonsingular system group.In the case of a local nonsingular system After the state estimation, the optimal weighted fusion algorithm in the sense of linear minimum variance is used to obtain the full-order optimal fusion filter and the smoother of the original system. Simulation results show that the fusion estimator is superior to each local estimator.