Distributed trust-based unscented Kalman filter for non-linear state estimation under cyber-attacks: The application of manoeuvring target tracking over wireless sensor networks

This paper is concerned with secure state estimation of non-linear systems under malicious cyber-attacks. The application of target tracking over a wireless sensor network is investigated. The existence of rotational manoeuvre in the target movement introduces non-linear behaviour in the dynamic model of the system. Moreover, in wireless sensor networks under cyber-attacks, erroneous information is spread in the whole network by imperilling some nodes and consequently their neighbours. Thus, they can deteriorate the performance of tracking. Despite the development of target tracking techniques in wireless sensor networks, the problem of rotational manoeuvring target tracking under cyberattacks is still challenging. To deal with the model non-linearity due to target rotational manoeuvres, an unscented Kalman filter is employed to estimate the target state variables consisting of the position and velocity. A diffusion-based distributed unscented Kalman filtering combined with a trust-based scheme is applied to ensure robustness against the cyber-attacks in manoeuvring target tracking applications over a wireless sensor network with secured nodes. Simulation results demonstrate the effectiveness of the proposed strategy in terms of tracking accuracy, while random attacks, false data injection attacks, and replay attacks are considered