Event-triggered Distributed Sequential Estimation for Wireless Sensor Networks

In this paper, we propose an event-triggered distributed sequential fusion estimator based on information filters. This algorithm not only uses the distributed parallel structure on sensors, but also uses the real-time processing of sequential fusion on state estimates. Therefore, it has the advantages of reliability and reduced computational burden. The event-triggered mechanism is designed based on observations of each sensor. Moreover, the equivalence on estimation accuracy of the proposed event-triggered distributed sequential fusion filter and event-triggered centralized fusion filter is proven. A simulation example shows the effectiveness of the proposed algorithm.