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This paper is concerned with the estimation of the direction and distance of sound sources with the MUSIC beamforming algorithm, and their tracking with the help of Kalman filter. Direction-of-arrival (DOA) estimations can be performed using a combination of acoustical focusing and beamforming. Distance estimation is usually not part of the process, but it is possible through an extension of the beamforming algorithm. MUSIC (Multiple Signal Classification) is a relatively fast and simple method to locate sound sources. It is based on the separation of the received signals’ cross-spectral matrix to signal and noise subspaces. We also use the Kalman filter and its extended non-linear version to track moving sound sources. We evaluate the performance of these methods through simulations in the MATLAB environment and measurements with unmanned aerial vehicles (UAV). DOA estimations and tracking are possible in both cases, but distance estimation is significantly more problematic in the latter. We aim to find the cause of the errors in the estimation during measurements, to develop a more robust method in the future. [ABSTRACT FROM AUTHOR]