A Multiple Sound Source Localization and Counting Method Based on the Kernel Density Estimator

An unambiguous signal processing algorithm when using a wide intermicrophone distance is proposed in this paper for simultaneously locating and counting multiple active sound sources. Based on the kernel density estimator, a multistage structure in the time-frequency domain is used to suppress the influence of spatial aliasing, then the pooled angular spectrum is combined with a peak search method having an updated cut-off threshold and a source merging module. Complete source localization and counting is realized through the combination of these two steps. Simulation results show that the proposed method has a more robust performance than the classic counterpart, especially in adverse environments with spatial aliasing, reverberation, and interference between different sound sources.