Outdoor acoustic drone localization and tracking over a simple built environment

In this work, acoustic localization and tracking of drones is investigated. Traditional sound source localization methods are employed, including time difference of arrival and beamforming angle of arrival methods, exploiting the acoustic characteristics of the drones to estimate their location. Of particular interest is the intrinsic harmonic sound emitted by the rotors of the drone. Kalman filtering is used for tracking and minimizing large position estimation errors. Outdoor measurements of various drones from a sparse number of microphones positioned in a simple built environment are studied. The evaluation metrics for drone localization and tracking are presented. The many factors that explain these results are discussed.