强噪声下基于加窗LASSO的声源定位方法

SOUND SOURCE LOCALIZATION METHOD BASED ON WINDOWED LASSO IN STRONG NOISE

  • 摘要: 传统声源定位方法往往容易受到低信噪比等不利声学条件的影响,难以同时实现定位的准确性与实时性,为此提出一种基于加窗最小绝对收缩选择算子(Least Absolute Shrinkage and Selection Operator,LASSO)的定位方法。采用加窗LASSO对音频信号进行稀疏分解来提取所包含的高能暂态与稳态成分,利用两者进行SRP-PHAT计算,实现目标声源的空间定位。实验结果表明,该方法可以有效抑制环境噪声,将定位误差保持在±10°左右;减小计算复杂度,将每帧的定位时间降低到1 s以下。

     

    Abstract: Traditional sound source localization methods are often susceptible to adverse acoustic conditions such as low signal-to-noise ratio, and it is difficult to achieve localization accuracy and real-time performance at the same time. Therefore, a sound source localization method based on windowed least absolute shrinkage and selection operator (LASSO) is proposed. The windowed LASSO was used to sparse decompose the audio signal to extract the high-energy transient and tonal components. The two components were used to calculate SRP-PHAT to realize the spatial localization of the target sound source. The experimental results show that the method can effectively suppress environmental noise and keep the positioning error at about ±10°. At the same time, the computational complexity is reduced, and the positioning time per frame is reduced to less than 1 s.

     

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