带未知通信干扰和丢包补偿的多传感器网络化不确定系统的分布式融合滤波  

Distributed Fusion Filtering for Multi-sensor Networked Uncertain Systems With Unknown Communication Disturbances and Compensations of Packet Dropouts

作　　者：祁波[1] 孙书利[1] QI Bo;SUN Shu-Li(School of Electronics Engineering, Heilongjiang University, Harbin 150080)

机构地区：[1]黑龙江大学电子工程学院,哈尔滨150080

出　　处：《自动化学报》2018年第6期1107-1114,共8页Acta Automatica Sinica

基　　金：国家自然科学基金(61174139;61573132);黑龙江省杰出青年基金(JC201412);黑龙江大学研究生创新科研项目(YJSCX2016-068HLJU)资助~~

摘　　要：研究了带有未知通信干扰、观测丢失和乘性噪声不确定性的多传感器网络化系统的状态估计问题.通过白色乘性噪声描述系统状态和观测中的随机不确定性,采用一组服从Bernoulli分布的随机变量描述网络传输过程中存在的观测丢失现象,且数据传输中存在未知的网络通信干扰.当发生丢包时,以当前丢失观测的预报值进行补偿.对每个单传感器子系统,应用线性无偏最小方差估计准则设计了不依赖于未知通信干扰的最优线性滤波器.推导了任两个局部滤波误差之间的互协方差阵.进而,应用矩阵加权融合估计算法给出了分布式融合状态滤波器.仿真例子验证了算法的有效性.This paper is concerned with the state estimation problem for multi-sensor networked systems with unknown communication disturbances, measurement losses and multiplicative noise uncertainties. The random uncertainties of the state and measurements of systems are described by white multiplicative noises. The phenomena of measurement losses during data transmissions through networks are described by a group of Bernoulli distributed random variables.Unknown communication disturbances exist in data transmissions. The predictors of the lost measurements are used as the compensation in the presence of packet losses. By applying the linear unbiased minimum variance estimation criterion, an optimal linear filter independent of unknown communication disturbances is designed for every single sensor subsystem.Filtering error cross-covariance matrices between any two local filters are derived. Further, a distributed fusion state filter is presented by using the matrix-weighted fusion estimation algorithm. A simulation example is given to verify the effectiveness of the proposed algorithms.

关 键 词：未知通信干扰 丢包补偿 乘性噪声 分布式融合滤波 多传感器网络化系统 

分 类 号：TN713[电子电信—电路与系统] TP212[自动化与计算机技术—检测技术与自动化装置]