Iterative Redeployment of Illumination and Sensing (IRIS): Application to STW-SAR Imaging

摘要

A new technique which we call Iterative Redeployment of Illumination and Sensing (IRIS) is introduced and applied to See-Through-the-Wall radar imaging. IRIS is applicable to adaptive sensing scenarios where the medium is illuminated and measured multiple times using different illuminator/sensor configurations, e.g., position, bandwidth, or polarization. These configurations are adaptively selected to minimize uncertainty in the image reconstruction. The IRIS algorithm has the following features: (1) use of a sparse Bayesian image model that captures the free-space dominated propagation characteristics of interiors of man-made structures such as caves and residences; (2) iterative reconstruction of both an image and an image confidence map from the posterior likelihood in the form of a thresholded Landweber recursion, (3) use of the Bayesian model to predict the best redeployment configuration of the illuminator platform given the current image and confidence map. For the STW application we approximate the forward operator by a matrix formulation of wavenumber migration. A simulated STW application is provided that illustrates the IRIS algorithm.