Fuzzy Logic-Based Target Classification Using Kinematic Data

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.