摘要
基于新息分析方法,对带有色观测噪声的多重时滞系统,提出了一种带自噪声估值器的非增广的最优滤波器.它等价于一个带相关白噪声多重时滞系统的一步预报器.当系统带有多个传感器时,推导了多重时滞系统的任意两个传感器子系统之间的估计误差互协方差阵.基于线性最小方差最优加权融合估计算法,给出了分布式加权融合最优滤波器.分布式融合估计比基于每个传感器的局部估计具有更高的精度.比增广的集中式最优滤波器具有更好的可靠性,且避免了高维计算和大存储空间.仿真例子验证了其有效性.
Based on the innovation analysis approach, a non-augmented optimal filter with a white noise estimator is presented for a multiple time-delay system with colored measurement noise. It is equivalent to the first-step predictor for a multiple time-delay system with correlated white noise. When the system contains multiple sensors, the estimation error cross-covariance matrix between any two sensor subsystems is derived for the multiple time-delay system. A distributed weighted fusion optimal filter is given based on the optimal weighted fusion estimation algorithm in the linear minimum variance sense. The distributed fusion filter has a higher accuracy than the local filter based on each sensor. It has better reliability than the centralized optimal filter by augmentation, and avoids the high-dimensional computation and the large space memory. An example shows its effectiveness.
出处
《自动化学报》
EI
CSCD
北大核心
2009年第1期46-53,共8页
Acta Automatica Sinica
基金
国家自然科学基金(60504034)
黑龙江省青年骨干教师基金(1151G035)资助~~
关键词
多重时滞系统
有色观测噪声
信息融合
分布式最优滤波器
Multi-delay system, colored measurement noise, information fusion, distributed optimal filter
