Distributed Estimation in Periodically Switching Sensor Networks

This paper studies the distributed estimation problem of sensor networks, in which each node is periodically sensing and broadcasting in order. A consensus estimation algorithm is applied, and a weight design approach is proposed. The weights are designed based on an adjusting parameter and the nodes’ lengths of their shortest paths to the target node. By introducing a (T+2)-partite graph of the time-varying networks over a time period [0,T] and studying the relationships between the product of the time-sequence estimation error system matrices and the sequences of edges in the (T+2)-partite graph, a sufficient condition in terms of the observer gain and the adjusting parameter for the stability of the estimation error system is proposed. A simulation example is given to illustrate the results