ABSTRACT

This chapter presents distributed fusion from the situation assessment (SA) perspective. It describes the relevance of distributed fusion to network-centric warfare environments and the role of intelligent agents in that context. The chapter explains an overall estimate of a target at a fusion center that combines estimates from distributed sensors located at different fusion nodes which are all tracking the same target. It utilizes the Kalman filter algorithm for estimating targets at local fusion nodes from sensor observations. Individual estimates from local fusion nodes are then combined at a fusion center, thereby generating evidence to be propagated into a Belief network model for SA. Some sensor networks consist of a large number of nodes of sensing devices, densely distributed over the operational environment of interest. Using pairwise communication-link information sent between neighbors in a spanning tree, the nodes compute the information necessary to transform the spanning tree into a junction tree for the inference problem.