Distributed event-triggered target tracking under cyber attacks

Distributed target tracking is an important problem in sensor networks (SNs). In this paper, the problem of distributed target tracking is addressed under cyber-attacks for targets with discrete-time and continuous-time nonlinear dynamics. Two distributed filters are obtained for every node of the SN to estimate the states of a general class of nonlinear targets which can be seen in many practical applications. Compared with the existing results in the literature, the network topology of the SN is assumed to be subjected to the denial-of-service attack such that the communication links among sensor nodes are paralyzed or destroyed by this kind of attack. Moreover, the proposed algorithms are designed based on an event-triggered communication strategy that means the frequency of information transmission and unnecessary resource consumption are significantly reduced. The presented algorithms' stability is also analyzed in the presence of noise to achieve secure event-triggered target tracking in mean-square. Two simulation examples are utilized to demonstrate the efficiency of the proposed event-triggered algorithms.