  Accurate motion capture of aerial robots in 3-D is a key enabler for
autonomous operation in indoor environments such as warehouses or factories, as
well as driving forward research in these areas. The most commonly used
solutions at present are optical motion capture (e.g. VICON) and Ultrawideband
(UWB), but these are costly and cumbersome to deploy, due to their requirement
of multiple cameras/sensors spaced around the tracking area. They also require
the drone to be modified to carry an active or passive marker. In this work, we
present an inexpensive system that can be rapidly installed, based on
single-chip millimeter wave (mmWave) radar. Importantly, the drone does not
need to be modified or equipped with any markers, as we exploit the Doppler
signals from the rotating propellers. Furthermore, 3-D tracking is possible
from a single point, greatly simplifying deployment. We develop a novel deep
neural network and demonstrate decimeter level 3-D tracking at 10Hz, achieving
better performance than classical baselines. Our hope is that this low-cost
system will act to catalyse inexpensive drone research and increased autonomy.
