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首页> 外文期刊>The Journal of the Acoustical Society of America >Adaptive eigenvalue decomposition algorithm for passive acoustic source localization
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Adaptive eigenvalue decomposition algorithm for passive acoustic source localization

机译:被动声源定位的自适应特征值分解算法

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To find the position of an acoustic source in a room, the relative delay between two (or more) microphone signals for the direct sound must be determined. The generalized cross-correlation method is the most popular technique to do so and is well explained in a landmark paper by Knapp and Carter. In this paper, a new approach is proposed that is based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the microphone signals contains the impulse responses between the source and the microphone signals (and therefore all the information we need for time delay estimation). In experiments, the proposed algorithm performs well and is very accurate.
机译:为了找到房间中声源的位置,必须确定直接声音的两个(或多个)麦克风信号之间的相对延迟。广义互相关方法是最受欢迎的技术,并且在Knapp和Carter的地标性论文中得到了很好的解释。本文提出了一种基于特征值分解的新方法。确实,与麦克风信号协方差矩阵的最小特征值相对应的特征向量包含源和麦克风信号之间的脉冲响应(因此,我们需要进行时延估计的所有信息)。在实验中,所提出的算法性能良好且非常准确。

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