  Automatic detection of flying drones is a key issue where its presence,
especially if unauthorized, can create risky situations or compromise security.
Here, we design and evaluate a multi-sensor drone detection system. In
conjunction with standard video cameras and microphone sensors, we explore the
use of thermal infrared cameras, pointed out as a feasible and promising
solution that is scarcely addressed in the related literature. Our solution
integrates a fish-eye camera as well to monitor a wider part of the sky and
steer the other cameras towards objects of interest. The sensing solutions are
complemented with an ADS-B receiver, a GPS receiver, and a radar module.
However, our final deployment has not included the latter due to its limited
detection range. The thermal camera is shown to be a feasible solution as good
as the video camera, even if the camera employed here has a lower resolution.
Two other novelties of our work are the creation of a new public dataset of
multi-sensor annotated data that expands the number of classes compared to
existing ones, as well as the study of the detector performance as a function
of the sensor-to-target distance. Sensor fusion is also explored, showing that
the system can be made more robust in this way, mitigating false detections of
the individual sensors.
