  The microwave imaging based on inverse scattering strategy holds important
promising in the science, engineering, and military applications. Here we
present a compressed-sensing (CS) inspired large- aperture computational
single-sensor imager using 1-bit programmable coding metasurface for efficient
microwave imaging, which is an instance of the coded aperture imaging system.
However, unlike a conventional coded aperture imager where elements on random
mask are manipulated in the pixel-wised manner, the controllable elements in
the proposed scheme are encoded in a column-row-wised manner. As a consequence,
this single-sensor imager has a reduced data-acquisition time with improved
obtainable temporal and spatial resolutions. Besides, we demonstrate that the
proposed computational single-shot imager has a theoretical guarantee on the
successful recovery of a sparse or compressible object from its reduced
measurements by solving a sparsity-regularized convex optimization problem,
which is comparable to that by the conventional pixel-wise coded imaging
system. The excellent performance of the proposed imager is validated by both
numerical simulations and experiments for the high-resolution microwave
imaging.
