A Compressive Deconvolution Approach for Microwave Single-Pixel Imaging

This work presents a retrieval algorithm intended for space-borne passive microwave single pixel imaging (MSPI). While prior work has focused on conventional sparse- regularization algorithms for retrieving brightness temperature scenes compressively sensed by MSPI [1], here we seek to expand the approach to mitigate resolution corruption introduced by the sensing patterns of the proposed aperture. We conduct a study of the approach using a compressive total-variation (TV) algorithm applied to model brightness temperature data and antenna patterns generated by a computational electromagnetic (EM) model. Early results indicate improvement in reconstruction quality.