Accounting for the Influence of Decorrelation in Microphone Phased Array Deconvolution Methods

Abstract

Microphone phased arrays are a common tool for use in aeroacoustic wind tunnel testing. The analysis of acquired array data is known to suffer from decorrelation effects, where the coherence of an acoustic wave measured by a pair of microphones is degraded as the wave passes through a turbulent free shear layer or boundary layer. This paper describes, in detail, how to mitigate the influence of decorrelation effects when processing array data with deconvolution methods. This is done using the DAMAS algorithm as an example, applied to recent airframe noise test data acquired in the NASA Langley 14- by 22-Foot Subsonic Tunnel. Two ways of handling the turbulent propagation modeling, both assuming plane wave propagation, are described. Results show that while turbulence model fit parameters may differ, both methods output extremely similar deconvolution results. Further improvements likely require more accurate mean shear layer data prior to developing more involved turbulence models.