Interception and detection of drones using RF-based dataset of drones

Abstract

The usage of Unmanned Aerial Vehicles (UAVs) is accessible for different applications to a wide range of users. However, this wide range of users raises a great concern about the threat (passive or active threats) of malicious actors who can use UAVs for criminal activities. The detection of UAVs is considered to be the first step in the process of UAVs countering (c-UAV). Nowadays, the c-UAV applications offer systems that include different sensors such as electro-optical, thermal, acoustic, radar and radio frequency sensors. Information gathered by these sensors can be fused in order to increase the reliability of threat's detection, classification and identification. It is necessary to have datasets from the different sensors in order to develop methods and algorithms for detection and classification of UAVs. This paper presents a dataset of communication signals between the drone and the control station that is used in the process of detection and classification.