LAUSR

In this letter, we propose an algorithm to estimate the distance between an aerial vehicle and a large obstacle using the self-induced noise present during the vehicle's normal operation. We demonstrate the feasibility of using the proposed estimation method in real-time as a feedback mechanism to actively control the altitude of a blimp-like vehicle. The method is built upon a physics-based acoustic model of an unknown source emitting sound near an acoustically reflective surface. By placing two microphones beneath a motor-propeller system used to control the altitude of the vehicle, a real-time processing algorithm of the audio signals is presented that can accurately detect the distance from the microphones to the ground. The method is based upon computing the cross-correlation matrix of the signals on the two microphone channels. We develop a novel cross-correlation processor that is capable of filtering out the unknown source term and extracting the relevant time-delay representing the time it takes for an acoustic wave traveling from the microphone to the ground and back. Furthermore, we show that the method is also robust to the more complex noise source generated by a quadrotor in a static, tethered experiment. To the best of our knowledge, this is the first framework and demonstration of obstacle sensing onboard an aerial vehicle using only the self-generated noise.