SAR imaging at low center frequencies (UHF and L-band) offers advantages over imaging at more conventional (X-band)
frequencies, including foliage penetration for target detection and scene segmentation based on polarimetric
coherency. However, bandwidths typically available at these center frequencies are small, affording poor resolution. By
exploiting extreme spatial diversity (partial hemispheric k-space coverage) and nonlinear bandwidth
extrapolation/interpolation methods such as Least-Squares SuperResolution (LSSR) and Least-Squares CLEAN
(LSCLEAN), one can achieve resolutions that are commensurate with the carrier frequency (λ/4) rather than the
bandwidth (c/2B). Furthermore, extreme angle diversity affords complete coverage of a target's backscatter, and a
correspondingly more literal image. To realize these benefits, however, one must image the scene in 3-D; otherwise
layover-induced misregistration compromises the coherent summation that yields improved resolution. Practically, one
is limited to very sparse elevation apertures, i.e. a small number of circular passes. Here we demonstrate that both LSSR
and LSCLEAN can reduce considerably the sidelobe and alias artifacts caused by these sparse elevation apertures.
Further, we illustrate how a hypothetical multi-static geometry consisting of six vertical real-aperture receive apertures,
combined with a single circular transmit aperture provide effective, though sparse and unusual, 3-D k-space support.
Forward scattering captured by this geometry reveals horizontal scattering surfaces that are missed in monostatic
backscattering geometries. This paper illustrates results based on LucernHammer UHF and L-band mono- and multi-static
simulations of a backhoe.