Micro-Doppler Signature-Based Detection, Classification, and Localization of Small UAV With Long Short-Term Memory Neural Network

Abstract

Along with the popularization of small unmanned aerial vehicles (UAVs), societal concerns related to security, privacy, and public safety have gained more attention, thus opening a new avenue for small UAV surveillance. However, the conventional radar technologies pose challenges for the surveillance of small UAVs due to the high cost, small radar cross section, low flying altitude, and slow flying speed. In this article, we propose a novel micro-Doppler signature-based surveillance method using machine learning techniques, for detection, classification, and localization of small UAVs. Via extensive experiments, we demonstrate the performance gain of our proposed method by applying long short-term memory neural network.