Algorithm for the Accurate Localization of Sounds

摘要

A computer-based algorithm that localizes sounds in near-real time has been developed. The algorithm takes input from two microphones and estimates the position of the sound source relative to the microphone array. The algorithm requires no a priori knowledge of the stimuli to be localized. The accuracy of the algorithm was tested using binaural recordings from a pair of microphones mounted in the ear canals of an acoustic mannequin. Sounds were played at 5 degree steps around the mannequin and the outputs were recorded at the entrance to each ear canal. These recordings were fed into the algorithm that estimated the location of the incoming sound on the horizontal plane. The algorithm utilizes a Head-Related Transfer Function (HRTF) to estimate the location of incoming sound stimuli. Although the HRTF of the acoustic mannequin was used, any HRTF can be inserted into the algorithm, allowing for predictions about individual performance differences. The results of this effort have been highly encouraging: the algorithm was able to identify accurately the location of a variety of sounds, committing an average of 2.9 degrees of unsigned localization error. Better than chance performance was found in noisy conditions of up to a -10 dB signal-tonoise ratio. The initial purpose of this algorithm is to predict the localization performance afforded by different types of combat helmets. Current and future encapsulating helmet designs are likely to impede localization performance, and an accurate localization model would be an invaluable tool in the helmet selection process. Adapting the model for use as a highly accurate machine-based localizer is an additional goal of this line of research. Applications for this technology include target tracking on unmanned vehicles, sniper detection, and machine-assisted sound localization.