网络攻击下无人机信息物理系统的自适应状态估计

Adaptive state estimate for unmanned aircraft cyber-physical system with cyber attack

针对网络攻击下无人机信息物理系统(CPS)的安全状态估计问题,提出了一种基于自适应方差极小化的递推状态估计器(AVMRE)。通过将针对控制输入和传感器数据的恶意攻击分别建模为状态和量测方程中的未知干扰项,建立了未知干扰解耦状态递推估计器,实现滤波误差中的量测未知干扰解耦,利用滤波残差设计自适应调整因子对估计误差上界进行极小化,应用最小方差估计准则求解出算法中的量测增益反馈矩阵。同时引入事件触发机制,使得系统在保持一定估计精度的情况下节省通信资源。此外,给出了滤波误差指数有界性的充分条件。无人机飞行模型仿真验证了本文算法相比传统算法的有效性和优越性。

An Adaptive-Variance-Minimization-based Recursive Estimator(AVMRE)is proposed for the problem of secure state estimation of Unmanned Aerial Vehicle(UAV)Cyber-Physical System(CPS).By modeling the data attacks on control commands and sensors as the unknown disturbances in the state and measurement equations respectively,an unknown disturbances decoupling state recursive estimator is established,which realizes the unknown measurement disturbances decoupling in filter error.Then,the adaptive adjust factor is designed by the filter residual to minimize the upper bound of the estimate error.Finally,the measurement gain feedback matrix in the algorithm is deduced based on the minimum variance estimation criterion.The distributed event-trigger mechanism is also considered,so that the system can save communication resources in the case of maintaining certain estimation accuracy.In addition,a sufficient condition for the filter error exponential boundedness is given.Simulation results of the UAV flight controller show the effectiveness and superiority of the proposed algorithm over traditional methods.