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The generalized cross-correlation with phase transform (GCC-PHAT) algorithm has proved to be useful for blindly estimating the direction of arrival of compact sound sources from microphone array recordings. In applications with distributions of partial sources, such as the tires of vehicles in urban environments, the GCC-PHAT needs to be improved, otherwise the detected sound directions change values between directions of the main sources or correspond to an intermediate value between these directions. This paper presents an extension of the GCC-PHAT, based on post-processing of the output delay matrix and on image processing techniques, in order to separately identify directions of the sound produced by the front and rear tires of moving vehicles. The proposed approach can be extended to identify the tire noise directions produced by vehicles with multiple axles. The algorithm performance is analyzed using pass-by measurements of two-axle vehicles, acquired by a two-microphone array. The experiments were conducted with passenger vehicles of four distinct models, running at different speeds. The experimental results show that the proposed method is able to estimate the vehicle speed with an average error of 10.8 km/h and the vehicle wheelbase with 26 cm on average. A possible application is multiple source characterization for parametric vehicle sound synthesis in auralization.

Direction of arrival estimation of partial sound sources of vehicles with a two-microphone array