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Several deconvolution algorithms are commonly used in aeroacoustics to estimate the power level radiated by static sources, for instance, the deconvolution approach for the mapping of acoustic sources (DAMAS), DAMAS2, CLEAN, and the CLEAN based on spatial source coherence algorithm (CLEAN-SC). However, few efficient methodologies are available for moving sources. In this paper, several deconvolution approaches are proposed to estimate the narrow-band spectra of low-Mach number uncorrelated sources. All of them are based on a beamformer output. Due to velocity, the beamformer output is inherently related to the source spectra over the whole frequency range, which makes the deconvolution very complex from a computational point of view. Using the conventional Doppler approximation and for limited time analysis, the problem can be separated into multiple independent problems, each involving a single source frequency, as for static sources. DAMAS, DAMAS2, CLEAN, and CLEAN-SC are then extended to moving sources. These extensions are validated from both synthesized data and real aircraft flyover noise measurements. Comparable performances to those of the corresponding static methodologies are recovered. All these approaches constitute complementary and efficient tools in order to quantify the noise level emitted from moving acoustic sources.

In regard to the problem of aircraft noise mitigation, the present study focuses on the refraction effects to be possibly induced by anechoic facility jet flows on the measured acoustic signatures, during typical airframe noise experiments. To this end, Computational AeroAcoustics (CAA) calculations based on the solving of the Perturbed Euler Equations (PEE) are conducted, enabling the estimation of the refraction effects characterizing a typical open-jet, anechoic wind tunnel, namely the NASA Langley's Quiet Flow Facility (QFF). Coming along with their validation against analytical results obtained through a Ray Tracing (RT) technique, the analysis of these CAA/PEE calculations highlights the refraction effects by the facility jet flow, delivering preliminary insights about what are the key parameters (jet height, jet curvature, jet spreading angle, shear layer thickness, etc.) to play a major role in these refraction phenomena.

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