Conventional synthetic aperture radar processes all of the available k-space data to form a single 2-D image. While this does yield the finest resolution image possible, it implicitly assumes that imaged scatterers lie within the chosen image plane and that their responses are isotropic over the observed k-space. These assumptions neglect out-of-plane height, which can lead to pixel phase and layover variation over the extent of an aperture, and other anisotropic scattering behaviors expected of non-point responses. The averaging process of image formation may therefore be destroying or obscuring data richness that is not easily recovered in later processing. In this paper, we show that subaperture processing of SAR data permits anisotropic scattering behavior, such as out-of-plane height, to be implicitly encoded in color channels, and through a few suggested approaches, we seek to improve image interpretability for humans and machine learning.
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