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

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  • Yuzhuo Fang
  • Xian Zang
  • Juan Yang
  • Hongcheng Zhou
  • Zhiyong Xu
  • Jelena Nikolić

Abstract

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.

Suggested Citation

  • Yuzhuo Fang & Xian Zang & Juan Yang & Hongcheng Zhou & Zhiyong Xu & Jelena Nikolić, 2022. "A Multiple Sound Source Localization and Counting Method Based on the Kernel Density Estimator," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, January.
    • Handle: RePEc:hin:jnlmpe:6783184
    DOI: 10.1155/2022/6783184
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