Acoustic Source Localization Based on Sparse Representation Using Image Model and its Experimental Verification
Lu Wang, Yanshan Liu, Guoan Bi · 2018
The paper presents the most recent progress on the research of acoustic source localization based on sparse representation using image model. The most critical problem of indoor acoustic source localization is the reverberation. The interference caused by reflections severely degrades the localization accuracy. Image model is one method that accurately models the reverberant acoustic field. Combining the image model with the sparse representation, high resolution acoustic localization can be achieved in strong reverberant environment. We present in this paper the models and fundamental theory of algorithms and conduct corresponding real experiments to verify their effectiveness.