基于差分麦克风阵列和语音稀疏性的多源方位估计方法

差分麦克风阵列为实现小尺寸阵列条件下的声源定位提供了一条重要技术途径。语音信号具有稀疏性，利用该特性可实现基于差分麦克风阵列的多声源方位估计，其中的典型方法为直方图法。针对差分麦克风阵列，本文提出了一种基于时频掩蔽和模糊聚类分析的短时平均复声强多声源方位估计方法。分析了不同阵列尺寸条件下时频掩蔽频带范围的选择问题。该方法具有闭式解，在强混响噪声环境下的性能优于直方图法，并且受阵列尺寸变化的影响较小。为了改善直方图法的性能，基于时频掩蔽的思想，文中还给出了一种修正的直方图方法。混响噪声环境下的仿真实验结果验证了本文所提方法的有效性。

Direction Finding of Multiple Sound Sources Based on Sparseness of Speech Signals and Differential Microphone Array

Differential microphone arrays have become a promising method to address multiple sound source localization. Among the differential microphone arrays, the existing typical method is the histogram approach, which utilizes the time-frequency sparseness characteristic of speech signals. A direction-finding algorithm for multiple sound sources by the short-time average complex sound intensity estimation is proposed based on time-frequency masking and fuzzy clustering. The frequency bounds for time-frequency masking under various array sizes are also discussed. The advantages of the proposed method are that it has closed-form solution, superior to the histogram approach, and also less sensitive to array size. Based on the idea of time-frequency masking, an improved histogram approach is also presented. The performance of the proposed methods is verified by simulation results under noisy and reverberant environment.