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.
