Incremental Noise Estimation in Outdoor Auditory Scene Analysis using a Quadrocopter with a Microphone Array

This paper addresses sound source localization using an aerial vehicle with a microphone array in an outdoor environment to realize outdoor auditory scene analysis. It, for instance, aims at finding distressed people in a disaster situation. In such an environment, noise is quite loud and dynamically-changing, and conventional microphone array techniques studied in the field of indoor robot audition are of less use. We, thus, proposed MUltiple SIgnal Classification based on incremental Generalized EigenValue Decomposition (iGEVD-MUSIC). It can deal with dynamically-changing high power noise by introducing incrementally-estimated noise correlation matrices. We developed a prototype system for the outdoor auditory scene analysis based on the proposed method using the Parrot AR.Drone with an 8ch microphone array and a Kinect device. Experimental results using the prototype system showed that dynamically-changing noise is properly suppressed with the proposed method even when the signal-to-noise ratio is less than 0dB in an outdoor/indoor environment with the hovering/moving AR.Drone.