Cooperative management of netted surveillance sensors

The design of air surveillance multisensor systems implies to solve two related problems. The first one, data fusion, defines the optimal way of combining detection, local tracks and attributes received from several sensors (multifunction radars, IFFs, ESMs) before presenting the information to the operator. This article is focused on the second problem, the coordinate task management of the deployed sensors, which allows the optimisation of the data acquisition process of the surveilled environment considering two different types of information: global or high-level knowledge, result of the data fusion process; and local, internal to each sensor (sensor load). The proposed management architecture uses distributed artificial intelligence (DAI) techniques to cope with the sensor coordination task, in particular the multiagent theory, in order to get a high degree of autonomy of each sensor. The decision-making process in each sensor is based on fuzzy reasoning systems