We have studied sound source localization, using a microphone array embedded on a UAV (unmanned aerial vehicle), for the purpose of detecting for people to rescue from disaster-stricken areas or other dangerous situations, and we have proposed sound source localization methods for use in outdoor environments. In these methods, noise robustness and real-time processing have a trade-off relationship, which is a problem to be solved for the practical application of the methods. Sound source localization in a disaster area requires both noise robustness and real-time processing. For this we propose a sound source localization method using an active frequency range filter based on the MUSIC (MUltiple Signal Classification) method. Our proposed method can successively create and apply a frequency range filter by simply using the four arithmetic operations, so it can ensure both noise robustness and real-time processing. As numerical simulations carried out to compare the successful localization rate and the processing delay with conventional methods have affirmed the usefulness of the proposed method, we have successfully produced a sound source localization method that has both noise robustness and real-time processing.
Research on the near field sound source localization method for small snapshots
