Padois Thomas, Berry Alain
GAUS-Department of Mechanical Engineering, Université de Sherbrooke, 2500 boulevard de l'université, Sherbrooke, Quebec J1K 2R1, Canada.
J Acoust Soc Am. 2015 Dec;138(6):3678-85. doi: 10.1121/1.4937609.
Microphone arrays and beamforming have become a standard method to localize aeroacoustic sources. Deconvolution techniques have been developed to improve spatial resolution of beamforming maps. The deconvolution approach for the mapping of acoustic sources (DAMAS) is a standard deconvolution technique, which has been enhanced via a sparsity approach called sparsity constrained deconvolution approach for the mapping of acoustic sources (SC-DAMAS). In this paper, the DAMAS inverse problem is solved using the orthogonal matching pursuit (OMP) and compared with beamforming and SC-DAMAS. The resulting noise source maps show that OMP-DAMAS is an efficient source localization technique in the case of uncorrelated or correlated acoustic sources. Moreover, the computation time is clearly reduced as compared to SC-DAMAS.
麦克风阵列和波束形成已成为定位气动声源的标准方法。反卷积技术已被开发出来以提高波束形成图的空间分辨率。声源映射反卷积方法（DAMAS）是一种标准的反卷积技术，它已通过一种称为声源映射稀疏约束反卷积方法（SC-DAMAS）的稀疏方法得到改进。在本文中，使用正交匹配追踪（OMP）来解决DAMAS逆问题，并将其与波束形成和SC-DAMAS进行比较。所得的噪声源图表明，在不相关或相关声源的情况下，OMP-DAMAS是一种有效的源定位技术。此外，与SC-DAMAS相比，计算时间明显减少。
