In this work, the application of the cross-correlation Green's function retrieval method for source localization and atmospheric acoustic tomography is presented. Open field experimental measurements of an acoustic source, with an impulsive waveform, are conducted for the evaluation of an array system. Of particular interest are the source localization and sound speed estimation capabilities of the array system. The cross-correlation delay-and-sum beamformer is used to estimate source directivity and sound speed. This beamformer inherently employs the cross-correlation Green's function retrieval method between a pair of receivers. The beamforming results adequately identify the various source directions as well as the scatterers along the propagation path. Reasonable sound speed estimates are obtained at the peak frequency of the retrieved Green's functions. In the case of atmospheric acoustic tomography, the estimated sound speed from the array system can serve as an average background sound speed in a tomographic inversion algorithm. Utilizing a tomographic inversion algorithm with radial basis functions and the estimated sound speed, the reconstruction of temperature and wind velocity profiles are demonstrated.
In this work, Green’s function retrieval and frequency-wavenumber methods are employed to enhance array plane-wave beamforming maps for acoustic source localization and range estimation in an outdoor environment. The crosscorrelation and multidimensional deconvolution Green’s function retrieval methods are used to improve the signal-to-noise ratio of the beamforming maps. The Stolt’s frequency-wavenumber migration method is adapted to the plane-wave beamforming map to find the source positions, applying frequency-wavenumber migration image to the Stolt spatial transformation mapping. Open field microphone array measurements of active and passive sources are investigated. Of particular interests are the accuracy of the estimated source position, the effects of multiple sources, and the image contrast of the beamforming maps.
In this work, Green's function retrieval and frequency-wavenumber methods are employed for multiple source localization in an outdoor environment. The Green's function retrieval methods are used to improve the signal-to-noise ratio of the beamforming maps. The frequency-wavenumber method is adapted to the plane-wave beamforming map to accurately localize real sources, while removing the appearance of ghost sources due to the data-association problem and mitigating missed detections for sources close together. Open field microphone array measurements of active and passive sources are investigated.
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