Adaptive distributed estimation

This paper considers the distributed estimation problem when the communication pattern among the agents is not known a priori. We assume a network of estimation agents which receive measurements from the environment. The estimation agents communicate with each other using schedules which may not be fixed a priori. The objective of each agent is to generate the best estimate at any moment based on the local data and information received from other agents. Because the network configuration and/or communication pattern may change, the fusion algorithm of each agent cannot be specified a priori but has to adapt to the structure of the network. A fusion algorithm which can adapt is presented in this paper. The algorithm is based on the partial information graph available to that agent and makes use of the estimates as well as the history of communication.