  There has been a rapid growth in the deployment of Unmanned Aerial Vehicles
(UAVs) in various applications ranging from vital safety-of-life such as
surveillance and reconnaissance at nuclear power plants to entertainment and
hobby applications. While popular, drones can pose serious security threats
that can be unintentional or intentional. Thus, there is an urgent need for
real-time accurate detection and classification of drones. In this article, we
perform a survey of drone detection approaches presenting their advantages and
limitations. We analyze detection techniques that employ radars, acoustic and
optical sensors, and emitted radio frequency (RF) signals. We compare their
performance, accuracy, and cost, concluding that combining multiple sensing
modalities might be the path forward.
