LAUSR

Abstract Acoustic source mapping usually involves planar microphone arrays and calculation points located on a surface at a certain distance with respect to the array. An implicit assumption that sources are located on this surface is therefore performed. However, in some application, such as aeroacoustic source identification, this assumption may be wrong and produce misleading results. For this reason, it is interesting to extend the common acoustic mapping techniques to three-dimensional volumetric mapping. Direct beamforming techniques are not suited for volumetric imaging due to poor spatial resolution in radial direction from the array centre. Therefore, more refined algorithms, like deconvolution techniques or inverse methods, are required to obtain intelligible and accurate results. This paper describes the use of inverse methods in the context of aeroacoustic three-dimensional volumetric noise imaging. An Equivalent Source Method is formulated, based on Iteratively Reweighted Least Squares and on Bayesian Regularization. Moreover, a novel approach based on CLEAN-SC as decomposition tool of Cross-Spectral-Matrix in coherent source components is presented. The method proposed is applied on an aircraft model in wind tunnel. Performance are preliminary assessed with simulated test cases. A comparative investigation in exploiting a single planar array or multiple planar arrays observing noise sources from different directions is performed.