Event-Driven Distributed Kalman-Consensus Filter with Limited Memory Information

Consider the problem that the estimation accuracy is inversely proportional to the energy consumption in process monitor with wireless sensor networks (WSNs), the concept of the time-efficiency window is proposed based on the relationship between timeliness and information efficiency. And then, an improved event-driven mechanism combined with this time-efficiency window (TEW) is also designed. Consequently, a novel event-driven distributed Kalman-consensus filter with time-efficiency window (TEDKF) is presented. By adjusting the length of the time-efficiency window, the effective historical data stored in each sensor is used to information fusion. And then, the lifetime of WSNs becomes longer on the condition that the similar filtering accuracy is achieved than that of the event-driven distributed Kalman-consensus filter (EDKF). Finally, a simulation example is given to show the effectiveness of the proposed filter.