Detection, Tracking, and Interdiction for Amateur Drones

Abstract

Unmanned aerial vehicles, also known as drones, are expected to play major roles in future smart cities, for example, by delivering goods and merchandise, serving as mobile hotspots for broadband wireless access, and maintaining surveillance and security. The goal of this survey article is to study various potential cyber and physical threats that may arise from the use of UAVs, and subsequently review various ways to detect, track, and interdict malicious drones. In particular, we review techniques that rely on ambient radio frequency signals (emitted from UAVs), radars, acoustic sensors, and computer vision techniques for detection of malicious UAVs. We present some early experimental and simulation results on range estimation of UAVs and receding horizon tracking of UAVs. Finally, we summarize common techniques that are considered for interdiction of UAVs.