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Design of robust differential microphone arrays with the Jacobi-Anger expansion

机译:具有Jacobi-Anger扩展功能的强大差分麦克风阵列设计

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摘要

Due to their small size, differential microphone arrays (DMAs) are very attractive. Moreover, they have been effective in combating noise and reverberation. Recently, a new class of DMAs of different orders have been developed with the MacLaurin's series and the frequency-independent patterns. However, the MacLaurin's series does not approximate well the exponential function, which appears in the general definition of the beampattern, when the intersensor spacing is not small enough. To circumvent this problem, we propose in this paper to approximate the exponential function with the Jacobi-Anger expansion. Based on this approximation and the frequency-independent Chebyshev patterns, we derive first-, second-, and third-order DMAs. Furthermore, in order to improve the robustness of DMAs against white noise amplification, we propose to use more microphones combined with minimum-norm filters. It is also shown that the Jacobi-Anger expansion is optimal from a mean-squared error perspective. Simulations are carried out to evaluate the performance of the proposed DMAs. (C) 2016 Elsevier Ltd. All rights reserved.
机译:由于其尺寸小,差分麦克风阵列(DMA)非常有吸引力。此外,它们在对抗噪音和混响方面也很有效。最近,利用MacLaurin系列和与频率无关的模式开发了一种新的不同阶数的DMA。但是,当传感器间距不够小时,MacLaurin系列的指数函数不能很好地逼近指数函数,该函数出现在波束图的一般定义中。为了解决这个问题,我们建议在本文中用Jacobi-Anger展开近似指数函数。基于这种近似和与频率无关的切比雪夫模式,我们得出一阶,二阶和三阶DMA。此外,为了提高DMA抵抗白噪声放大的鲁棒性,我们建议使用更多的麦克风与最小范数滤波器组合。从均方误差的角度来看,Jacobi-Anger展开是最佳的。进行仿真以评估所提出的DMA的性能。 (C)2016 Elsevier Ltd.保留所有权利。

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