An improved acoustic deconvolution method for localizing correlated sound sources

被引：0
作者：
Wei L. [1 ]
Qin Z. [1 ]
Ren F. [1 ]
Zhang Z. [1 ]
Li M. [2 ,3 ]
Liu X. [4 ]
机构：
[1] Science and Technology on Reliability and Environment Engineering Laboratory, Beijing Institute of Structure and Environment Engineering, Beijing
[2] Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing
[3] Key Laboratory of Fluid Interaction with Material, Ministry of Education, University of Science and Technology Beijing, Beijing
[4] PLA 91550 Unit, Dalian
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2019年 / 40卷 / 11期
关键词：
Acoustic deconvolution; D-MACS; Microphone arrays; Noise measurement; Sound source localization;
D O I：
10.7527/S1000-6893.2019.23100
中图分类号：
学科分类号：
摘要：
In aerodynamic noise tests, the performance of sound source localization algorithm determines the accuracy of the localization of aeroacoustic sources. In this paper, D-MACS(Developed-Mapping of Acoustic Correlated Sources), an improved acoustic deconvolution method for the localization of the correlated sound sources, is proposed to enhance the robustness and accuracy when localizing the acoustic correlated sources. The characteristics of this new method are as follows. Base on the traditional MACS algorithm, the acoustic deconvolution model is adapted, forming a mathematical relationship between the cross-spectrum beamforming matrix and the covariance matrix of sound pressure at the observation points. And the sound source localization result obtained by this proposed method can increase the robustness and accuracy of the MACS method. Using the simulated sound source signals and that of the experimental data obtained in an acoustic wind tunnel, four methods including DAS(Delay And Sum beamformming), DAMAS-C(Deconvolution Approach for the Mapping of Acoustic Correlated Sources), MACS and D-MACS are compared in terms of their ability to localize the sound sources, verifying the superiority of D-MACS in sound source localization. © 2019, Press of Chinese Journal of Aeronautics. All right reserved.
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