Distributed Kalman consensus filtering algorithm based on event-driven

Considering the fact that each wireless senor node owns limited power in wireless sensor networks, a new type of distributed Kalman-consensus filtering algorithm based on event-driven is proposed for reducing energy consumption. This event-driven scheme is triggered by the updated covariance which is commonly used to describe errors between the true value and the estimated one. In this scheme, each sensor node communicates with its neighbour nodes when the updated covariance exceeds a given threshold for ensuring the filtering accuracy, otherwise not communicates for saving energy. Moreover, this scheme has self-adaptive function to adjust times of connection among nodes according to different given filtering accuracies. Consequently, this algorithm can save energy of nodes effectively and thus prolong the life of wireless sensor networks under the condition of guaranteeing enough filtering accuracy.