Symbolic Processing for Coordinated Task Management in Multiradar Surveillance Networks

In this contribution a fuzzy management system is developed to cope with the problem of evaluating multisensor tasks in defence surveillance applications. Based on all the surveilled track and sector data, a reasoning system will be developed which determines the priority of each surveillance task to be performed in each decision cycle by means of a symbolic inference process similar to that which would perform a human operator. This approach allows to integrate high-level information (not only numerical) in the decision process considering its uncertainty and possibly being subjective. The formal method elected to represent the variables involved in this decision process is the theory of possibility and fuzzy sets. The evaluation of this reasoning system has allowed to demonstrate the validity of this methodology to cope with the task management problem. The results demonstrate how the importance of the tasks, measured through their priority, allows the multisensor manager to adapt the coordination process to changing environments.