Application of multisource discrimination to the HELS method

Abstract

In most engineering applications, the acoustic fields are usually generated by multiple incoherent sources. When such acoustic fields are sampled and taken as input data to the Helmholtz equation least-squares (HELS) formulations directly, the reconstruction might not be accurate. Hence there is a need to discriminate the contributions from individual sources and separate the composite sound field into a set of spatially coherent subfields that are also mutually incoherent. In this paper, we apply the principal component decomposition technique to the HELS method to reconstruct acoustic radiation from multiple incoherent sources in a free field. The key ingredients of this technique include a diagonalization by singular value decomposition (SVD) of the cross-spectral matrices generated by a number of reference microphones. Each diagonal term corresponds to a subfield that results from a so-called virtual sound source. Even though such virtual sources are not always representative of the actual sources, they are nonetheless incoherent and thus can be used as input to HELS. Experimental validations of this technique on reconstructing acoustic pressure and time-averaged normal acoustic intensity on the surfaces of multiple incoherent sources are presented. [Work supported by NSF.]