Recursive Filtering for Complex Networks Against Random Deception Attacks
Cong Meng, Wenling Li · 2018
This paper is concerned with the recursive filtering problem for a class of discrete-time complex networks with randomly occuring deception attacks. A set of random variables that obey Bernoulli distribution have been introduced to describe the phenomenon of randomly occuring deception attacks. A coupled unscented Kalman filter (UKF) is developed where the sigma points of the UKF are propagated by introducing the coupled terms. The randomly occuring deception attacks scheme is designed in the framework of the UKF. A numerical example involving tracking of multiple interacting targets is provided to verify the effectiveness of the proposed filter.