Noise source identification by spherical beamforming based on sound pressure spherical harmonics decomposition

The beamforming algorithm for spherical microphone arrays based on sound pressure spherical harmonics decomposition can identify simultaneously noise sources from all directions in three-dimensional space, especially in cabin. A performance simulation of noise source identification was carried out for the typical rigid spherical array with 50 microphones. The results showed that the truncated length of the spherical harmonics, frequency and position of the noise sources had significant effects on the response of arrays, the optimal truncated length was 5 and the maximum MSL was up to -15.35 dB at 2 000 Hz. Furthermore, software for analyzing the dynamic performance of spherical array and imaging the acoustic sources was developed. The test example imaging of a given source using the software proves that the algorithm and the software is accurate.