Zhao Sipei, Ma Fei
Centre for Audio, Acoustics and Vibration, Faculty of Engineering and IT, University of Technology Sydney, Sydney, Australia.
J Acoust Soc Am. 2024 Jul 1;156(1):405-415. doi: 10.1121/10.0027915.
Acoustic beamforming aims to focus acoustic signals to a specific direction and suppress undesirable interferences from other directions. Despite its flexibility and steerability, beamforming with circular microphone arrays suffers from significant performance degradation at frequencies corresponding to zeros of the Bessel functions. To conquer this constraint, baffled or concentric circular microphone arrays have been studied; however, the former need a bulky baffle that interferes with the original sound field, whereas the latter require more microphones that increase the complexity and cost, both of which are undesirable in practical applications. To tackle this challenge, this paper proposes a circular microphone array equipped with virtual microphones, which resolves the performance degradation commonly associated with circular microphone arrays without resorting to physical modifications. The sound pressures at the virtual microphones are predicted from those measured by the physical microphones based on an acoustics-informed neural network, and then the sound pressures measured by the physical microphones and those predicted at the virtual microphones are integrated to design the beamformer. Experimental results demonstrate that the proposed approach not only eliminates the performance degradation but also suppresses spatial aliasing at high frequencies, thereby underscoring its promising potential.
声束形成旨在将声信号聚焦到特定方向，并抑制来自其他方向的不良干扰。尽管具有灵活性和可控性，但圆形麦克风阵列的波束形成在对应于贝塞尔函数零点的频率处会出现显著的性能下降。为克服这一限制，人们研究了带障板的或同心圆形麦克风阵列；然而，前者需要一个庞大的障板，这会干扰原始声场，而后者需要更多的麦克风，这会增加复杂性和成本，在实际应用中这两者都是不可取的。为应对这一挑战，本文提出了一种配备虚拟麦克风的圆形麦克风阵列，该阵列无需进行物理修改即可解决通常与圆形麦克风阵列相关的性能下降问题。基于声学信息神经网络，根据物理麦克风测量的声压预测虚拟麦克风处的声压，然后将物理麦克风测量的声压与虚拟麦克风处预测的声压进行整合，以设计波束形成器。实验结果表明，所提出的方法不仅消除了性能下降，还抑制了高频处的空间混叠，从而凸显了其广阔的应用前景。
