传感器带未知输入的离散随机线性系统的分布式融合滤波  

Distributed Fusion Filter for Discrete-time Stochastic Linear Systems with Unknown Sensor Inputs

作　　者：白锦花[1] 孙书利[1] 

机构地区：[1]黑龙江大学电子工程学院自动化系,哈尔滨150080

出　　处：《科学技术与工程》2008年第17期4816-4820,4832,共6页Science Technology and Engineering

基　　金：国家自然科学基金项目(60504034);黑龙江省青年骨干教师基金(1151G035)资助

摘　　要：对传感器含未知输入和带相关噪声的离散随机线性系统,在没有未知输入的任何先验信息的情况下,设计了线性最小方差无偏状态滤波器。当系统带有多个传感器时,推得了任两个传感器子系统的滤波误差的互协方差阵。进而基于多传感器线性最小方差标量加权融合算法,给出了标量加权分布式融合状态滤波器。仿真研究验证了其有效性。An unbiased state filter in the linear minimum variance sense is developed for discrete-time stochastic linear systems with unknown sensor inputs and correlated noises, where there is not any prior information for the unknown inputs. When there are multiple sensors, the cross-covariance matrix of filtering errors between any two sensors is derived. Further, the distributed scalar-weighted fusion state filter is given based on the multi-sensor optimal fusion algorithm in the linear minimum variance sense. A simulation example shows the effectiveness.

关 键 词：未知输入 信息融合 多传感器 互协方差阵 分布式融合滤波器. 

分 类 号：TN911.72[电子电信—通信与信息系统]