An intelligent algorithm for coherent sound source localization based on a strong tracking filter

Abstract

Background noise is inevitable when sensor arrays are used for aeroacoustic measurements in wind tunnels. The direct removal of background noise, however, would affect the measurement accuracy. In particular, the existing array signal processing algorithms are either invalid or inefficient for removing the noise that is coherent with the signal of interest. In this paper, an intelligent algorithm is developed to localize the coherent sound sources and background noise in real time by iteratively checking the collected data from the array. The proposed method can automatically adjust the suboptimal fading factor to extract useful information as much as possible in residual sequence. This algorithm is tested in simulations and then demonstrated in an experiment. Compared to the two existing methods, the results indicate that the new method has a good phase-shift tracking ability and rapid estimation-error convergence speed, and can achieve an acceptable performance even for low-cost acoustic sensors. Overall, the proposed method should assist array beamforming and hence benefit aeroacoustic measurement.