A method for obstacle detection using the sound that a drone naturally emits is proposed.  The sound emitted from a vehicle, ego-noise, is often considered a complicating factor for mission fulfilment, without purpose.  The idea in this paper is to utilise this ego-noise for obstacle detection, being the first to perform practical experiments of this.  Adding a few microphones to the vehicle, the ego-noise is utilised as the sound source for echolocation.  The method consists of auto-correlating the received signals to estimate echo delays, using the known array geometry and signal propagation speed to relate delays to distances, and then beamforming to position targets.  A proof-of-concept has been constructed, and promising results are presented for experiments in a controlled environment.