State Key Laboratory of Turbulence and Complex Systems, Department of Aeronautics and Astronautics, Peking University, Beijing, 100871, China.
J Acoust Soc Am. 2012 Mar;131(3):2152-61. doi: 10.1121/1.3682041.
Phased microphone arrays have become an important tool in the localization of noise sources for aeroacoustic applications. In most practical aerospace cases the conventional beamforming algorithm of the delay-and-sum type has been adopted. Conventional beamforming cannot take advantage of knowledge of the noise field, and thus has poorer resolution in the presence of noise and interference. Adaptive beamforming has been used for more than three decades to address these issues and has already achieved various degrees of success in areas of communication and sonar. In this work an adaptive beamforming algorithm designed specifically for aeroacoustic applications is discussed and applied to practical experimental data. It shows that the adaptive beamforming method could save significant amounts of post-processing time for a deconvolution method. For example, the adaptive beamforming method is able to reduce the DAMAS computation time by at least 60% for the practical case considered in this work. Therefore, adaptive beamforming can be considered as a promising signal processing method for aeroacoustic measurements.
相控麦克风阵列已成为航空声学应用中声源定位的重要工具。在大多数实际的航空航天情况下,已经采用了延迟求和型的传统波束形成算法。传统的波束形成不能利用噪声场的知识,因此在存在噪声和干扰的情况下分辨率较差。自适应波束形成已被用于解决这些问题已有三十多年了,并在通信和声纳等领域已经取得了不同程度的成功。在这项工作中,讨论了一种专门为航空声学应用设计的自适应波束形成算法,并将其应用于实际的实验数据。结果表明,自适应波束形成方法可以为解卷积方法节省大量的后处理时间。例如,自适应波束形成方法能够将 DAMAS 计算时间减少至少 60%,对于本文考虑的实际情况。因此,自适应波束形成可以被认为是航空声学测量的一种很有前途的信号处理方法。