Wavenumber–frequency deconvolution of aeroacoustic microphone phased array data of arbitrary coherence

Abstract

Deconvolution of aeroacoustic data acquired with microphone phased arrays is a computationally challenging task for distributed sources with arbitrary coherence. A new technique for performing such deconvolution is proposed. This technique relies on analysis of the array data in the wavenumber–frequency domain, allowing for fast convolution and reduced storage requirements when compared to traditional coherent deconvolution. A positive semidefinite constraint for the iterative deconvolution procedure is implemented and shows improved behavior in terms of quantifiable convergence metrics when compared to a standalone covariance inequality constraint. A series of simulations validates the method׳s ability to resolve coherence and phase angle relationships between partially coherent sources, as well as determines convergence criteria for deconvolution analysis. Simulations for point sources near the microphone phased array show potential for handling such data in the wavenumber–frequency domain. In particular, a physics-based integration boundary calculation is described, and can successfully isolate sources and track the appropriate integration bounds with and without the presence of flow. Magnitude and phase relationships between multiple sources are successfully extracted. Limitations of the deconvolution technique are determined from the simulations, particularly in the context of a simulated acoustic field in a closed test section wind tunnel with strong boundary layer contamination. A final application to a trailing edge noise experiment conducted in an open-jet wind tunnel matches best estimates of acoustic levels from traditional calculation methods and qualitatively assesses the coherence characteristics of the trailing edge noise source.