A covariance fitting approach for correlated acoustic source mapping

• DOI: 10.1121/1.3365260
• Publication Date: 2010-05-13T21:47:47Z
• Authors: Tarik Yardibi; Jian Li; Petre Stoica; Nikolas S. Zawodny; Louis N. Cattafesta
• Keywords: Time Factors; Aircraft; Fourier Analysis; Reproducibility of Results; Signal Processing, Computer-Assisted; Acoustics; Equipment Design; Models, Theoretical; 01 natural sciences; Motion; Sound; Noise, Transportation; 0103 physical sciences; Pressure; Transducers, Pressure; Computer Simulation; Algorithms

Microphone arrays are commonly used for noise source localization and power estimation in aeroacoustic measurements. The delay-and-sum (DAS) beamformer, which is the most widely beamforming algorithm practice, suffers from low resolution high sidelobe level problems. Therefore, deconvolution approaches, such as approach mapping of acoustic sources (DAMAS), often extracting actual powers contaminated DAS results. However, approaches assume that uncorrelated. Although algorithms can deal with correlated sources, DAMAS do exist, these computationally impractical even small scanning grid sizes. This paper presents a covariance fitting (MACS), work uncorrelated, partially or coherent reasonably computational complexity. MACS minimizes quadratic cost function cyclic manner by making use convex optimization sparsity, guaranteed to converge at least locally. Simulations experimental data acquired University Florida Aeroacoustic Flow Facility 63-element logarithmic spiral microphone array absence flow demonstrate performance MACS.