为了在带反射边界的普通房间内重现声场,需要对原始声场信号进行去卷积处理,以获得扬声器驱动信号。本文建立了房间内声场重现的时域模型,在模型中采用长时长的去卷积网络,以获得高精度同时抑制了时域混叠效应,再针对卷积滤波的海量计算问题使用了快速滤波算法,提高了计算效率。汽车车内加速噪声的重现实验结果表明:本文所提出的时域模型可以高效准确地完成声压信号的去卷积化,实现普通房间内声场的定量重现。
Abstract
In order to reproduce a desired sound field in an ordinary room with reflection boundary, deconvolution of the desired sound field signals is neccessary to get the loudspeaker driving signals. In this research, a time-domain model used for sound field reproduction in a room is established. In the model, long-time deconvolution network is used to acquire high accuracy and avoid the time-domain aliasing effect at the same time. On account of the massive computation of the convolution process, fast filtering method is applied to improve the computational efficiency. The reproduction experiment of the interior noise in an acceleration vehicle indicates that the proposed time-domain model is able to implement the deconvolution of the sound pressure signals precisely and efficiently, and then implement the quantificational reproduction of the desired sound field in an ordinary room.
关键词
声场重现 /
非自由场 /
去卷积 /
滤波器设计 /
快速卷积
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Key words
sound field reproduction /
unfree field /
deconvolution /
filter design /
fast convolution
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参考文献
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