扩展卡尔曼滤波在受到恶意攻击系统中的状态估计  

Extended Kalman Filtering in State Estimation Systems With Malicious Attacks

作　　者：周雪 张皓[1] 王祝萍[1] ZHOU Xue;ZHANG Hao;WANG Zhu-Ping(Department of Control Science and Engineering,Tongji Uni-versity,Shanghai 200092)

机构地区：[1]同济大学控制科学与工程系

出　　处：《自动化学报》2020年第1期38-46,共9页Acta Automatica Sinica

基　　金：国家自然科学基金(61922063,61773289);上海自然科学基金(17ZR1445800,19ZR1461400);上海曙光计划(18SG18)资助~~

摘　　要：设计了一种分布式扩展卡尔曼滤波器(Extended Kalman lter,EKF),对非线性目标状态进行估计.在设计过程中,对滤波误差上界进行优化,获得了最优滤波增益.此外,在通信过程中,考虑恶意攻击信号的同时引入了分布式事件触发机制,使得系统在保持一定的估计精度的情况下节省通信资源.最后,以室内的机器人定位问题为例,验证了提出的滤波器的有效性.A distributed extended Kalman lter(EKF)is designed to estimate the nonlinear target state.In the design process,the optimal ltering gain is obtained by optimizing the upper bound of error covariance.In the process of communication,the distributed event-trigger mechanism is introduced meanwhile the malicious attack signal is considered,so that the system can save the communication resources in the case of maintaining certain estimation accuracy.Finally,an indoor robot localization problem is used to verify the e ectiveness of the proposed method.

关 键 词：分布式事件触发 扩展卡尔曼滤波 状态估计 恶意攻击 

分 类 号：TN713[电子电信—电路与系统] TP309[自动化与计算机技术—计算机系统结构]