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Accurate motion capture of aerial robots in 3-D is a key enabler forautonomous operation in indoor environments such as warehouses or factories, aswell as driving forward research in these areas. The most commonly usedsolutions at present are optical motion capture (e.g. VICON) and Ultrawideband(UWB), but these are costly and cumbersome to deploy, due to their requirementof multiple cameras/sensors spaced around the tracking area. They also requirethe drone to be modified to carry an active or passive marker. In this work, wepresent an inexpensive system that can be rapidly installed, based onsingle-chip millimeter wave (mmWave) radar. Importantly, the drone does notneed to be modified or equipped with any markers, as we exploit the Dopplersignals from the rotating propellers. Furthermore, 3-D tracking is possiblefrom a single point, greatly simplifying deployment. We develop a novel deepneural network and demonstrate decimeter level 3-D tracking at 10Hz, achievingbetter performance than classical baselines. Our hope is that this low-costsystem will act to catalyse inexpensive drone research and increased autonomy.

3-D Motion Capture of an Unmodified Drone with Single-chip Millimeter Wave Radar