Track Based UAV Classification Using Surveillance Radars

With their rapid technological developments, Unmanned Aerial Vehicles (UAVs), and micro UAVs have become a significant threat for homeland security and air defense systems. In air defense applications, classification of UAVs and discrimination of UAV tracks from non-UAV ones have become necessary. The classification of UAVs in the presence of heavy spatio-temporally varying radar clutter and interference across rural and urban areas, or under different weather conditions such as rain or snow is particularly challenging. In this paper, a classification method for UAV vs. non-UAV target discrimination, and micro-UAV classification using kinematic and Radio Frequency (RF) characteristics is proposed. For three different classes, namely, micro UAV-1, micro UAV-2 and non-UAV, various classifier architectures are implemented and the results based on real radar data are presented.