Distributed H∞ Filtering with Consensus Strategies in Sensor Networks: Considering Consensus Tracking Error

The existing distributed filtering with consensus strategies consists of two steps: the consensus step through locally communicating with neighboring sensor nodes and the local filtering step. In this paper, the influence of consensus tracking error on the local estimation error is analyzed, and a distributed H∞ filtering algorithm considering the consensus tracking error is proposed. When the number of consensus iterations per sampling period is limited, the proposed method can suppress the effect of consensus tracking error on local estimation error; when the number of consensus iterations per sampling period goes to infinity, i.e., the consensus tracking error converges to zero, the local filtering in the distributed algorithm reduces to the centralized filtering. Simulation shows the effectiveness of the proposed method.