Convolutional neural networks-based aerial target classification using micro-Doppler profiles

In this paper, convolutional neural networks (CNN)-based aerial target recognition is studied by exploiting the targets' micro-Doppler profiles. In order to simulate the targets' scatterings accurately, their realistic computer-aided design (CAD) models are considered. Scattering characteristics of the targets are taken into account for a variety of radar aspects and propeller or blade rotation speeds. Simulation results exhibit that CNN-based schemes would provide raised high speed in aerial target recognition area due to their self-feature learning nature.