Sound Source Tracking Using Integrated Direction Likelihood for Drones with Microphone Arrays

This paper presents a method for sound source localization and tracking using drones with microphone arrays. Signal processing with multiple microphone arrays enables us to estimate the sound source location via triangulation strategies. However in drone applications, triangulation approaches have difficulties in stable estimation of direction due to drone noise. Accordingly, we propose a novel method we call PArticle Filtering with Integrated MUSIC (PAFIM). PAFIM uses the strategy of direct localization which estimates the location likelihood distribution rather than estimating sound source directions. In this way, sound source locations can be estimated robustly than discrete triangulation. Numerical simulations demonstrated that PAFIM is effective in tracking moving sound sources with a root mean square error within 15% of sound source distance.