Abstract
The need for fast and accurate decisions in activities related to air surveillance and control has led to the development of systems to reduce operators' workload. In this context, a solution for aerial target classification is presented, using kinematic data (speed and acceleration) as input parameters. These can be estimated by a system composed of primary surveillance radar and a tracking algorithm. The implemented classifier is based on a fuzzy inference system that is capable of giving in real-time the membership degrees of a target to three defined classes, which is useful in the absence of data from secondary/IFF (Identification Friend or Foe) radars or imaging sensors.
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