Synthetic aperture acoustic imaging with deep generative model

Abstract

An acoustic imaging system includes a controller. The controller may be configured to receive a signal from a microphone and reverberation channel data, update latent variables, latent labels, a source amplitude, and a phase estimation based on an optimization of the signal and reverberation channel data to obtain updated latent variables, updated latent labels, an updated source amplitude, and an updated phase estimation, generate, via a conditional generative adversarial network (cGAN) of the updated latent variables and the updated latent labels, an acoustic source map tuned via the updated source amplitude and the updated phase estimation, optimize the acoustic source map, and output the optimized acoustic source map.