Extension of deconvolution algorithms for the mapping of moving acoustic sources

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.