Outdoor auditory scene analysis using a moving microphone array embedded in a quadrocopter

This paper addresses auditory scene analysis, especially, sound source localization using an aerial vehicle with a microphone array in an outdoor environment. Since such a vehicle is able to search sound sources quickly and widely, it is useful to detect outdoor sound sources, for instance, to find 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 high power noise by introducing a noise correlation matrix and GEVD even when the signal-to-noise ratio is less than 0 dB. In addition, the noise correlation matrix is incrementally estimated to adapt to dynamic changes in noise. We developed a prototype system for auditory scene analysis based on the proposed method using the Parrot AR.Drone with a microphone array and a Kinect device. Experimental results using the prototype system showed that dynamically-changing noise is properly suppressed with the proposed method and multiple human voice sources are able to be localized even when the AR.Drone is moving in an outdoor environment.