Distributed cubature information filtering based on hybrid consensus strategy with event-triggered mechanism

In this paper, the cubature information filtering is investigated to deal with the distributed state estimation problem for nonlinear systems. In order to release the communication burden of sensor networks, a new event-triggered mechanism is designed based on the difference between innovations at current time instant and the latest event-triggered time instant. The hybrid consensus strategy with the new event-triggered mechanism is adopted to leverage information from neighbor nodes, which combines the advantages of the consensus on measurements method and the consensus on information method. Finally, the effectiveness of the proposed algorithm is verified by a simulation.