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Direction of Arrival Estimation of Reflections from Room Impulse Responses Using a Spherical Microphone Array

机译:使用球形麦克风阵列从房间脉冲响应中反射的到达估计方向

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This paper studies the direction of arrival estimation of reflections in short time windows of room impulse responses measured with a spherical microphone array. Spectral-based methods, such as multiple signal classification (MUSIC) and beamforming, are commonly used in the analysis of spatial room impulse responses. However, the room acoustic reflections are highly correlated or even coherent in a single analysis window and this imposes limitations on the use of spectral-based methods. Here, we apply maximum likelihood (ML) methods, which are suitable for direction of arrival estimation of coherent reflections. These methods have been earlier developed in the linear space domain and here we present the ML methods in the context of spherical microphone array processing and room impulse responses. Experiments are conducted with simulated and real data using the em32 Eigenmike. The results show that direction estimation with ML methods is more robust against noise and less biased than MUSIC or beamforming.
机译:本文研究了用球形麦克风阵列测量的房间脉冲响应的短时间窗口中反射的到达估计方向。基于频谱的方法,例如多信号分类(MUSIC)和波束成形,通常用于分析空间房间脉冲响应。但是,室内声学反射在单个分析窗口中是高度相关或连贯的,这对基于频谱的方法的使用施加了限制。在这里,我们应用最大似然(ML)方法,该方法适用于相干反射的到达方向估计。这些方法是在线性空间域中较早开发的,这里我们在球形麦克风阵列处理和房间冲激响应的背景下介绍ML方法。使用em32 Eigenmike对模拟和真实数据进行实验。结果表明,与MUSIC或波束成形相比,使用ML方法进行方向估计对噪声更鲁棒,并且偏差更小。

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