iMAP Beamforming for High Quality High Frame Rate Imaging. (arXiv:1806.03526v1 [cs.IT])

We present a statistical interpretation of beamforming to overcome limitations of standard delay-and-sum (DAS) processing. Both the interference and the signal of interest are viewed as random variables and the distribution of the signal of interest is exploited to maximize the a-posteriori distribution of the aperture signals. In this formulation the beamformer output is a maximum-a-posteriori (MAP) estimator of the signal of interest. We provide a closed form expression for the MAP beamformer and estimate the unknown distribution parameters from the available aperture data using an empirical Bayes approach. We propose a simple scheme that iterates between estimation of distribution parameters and computation of the MAP estimator of the signal of interest, leading to an iterative MAP (iMAP) beamformer. This results in a significant improvement of the contrast compared to DAS without severe increase in computational complexity or need for fine-tuning of parameters. By implementing iMAP 查看全文>>