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Unmanned air vehicles often produce significant noise from their propulsionsystems. Using this broadband signal as "acoustic illumination" for anauxiliary sensing system could make vehicles more robust at a minimal cost. Wepresent an acoustic beamforming-based algorithm that estimates object-relativedistance with a small two-microphone array using the generated propulsionsystem noise of a vehicle. We demonstrate this approach in several closed-loopdistance feedback control tests with a mounted quad-rotor vehicle in a noisyenvironment and show accurate object-relative distance estimates more than 2xfurther than the baseline channel-based approach. We conclude that thisapproach is robust to several practical vehicle and noise situations and showspromise for use in more complex operating environments.

Acoustic Beamforming for Object-relative Distance Estimation and Control in Unmanned Air Vehicles using Propulsion System Noise