Radiative transfer is commonly modeled as the propagation of unpolarized radiation. More accurate approaches
utilizing polarimetric quantities are usually only applied to sensors that purposefully discriminate polarimetric
information. In this paper, we examine the effect on fidelity of utilizing polarimetric radiative transfer modeling for
non-polarimetric sensors. We show that if the primary irradiance on a scene is significantly polarized (such as sky
irradiance) then polarimetric radiative transfer modeling is warranted and provides a significant increase in fidelity. We
demonstrate this effect by performing target detection of shadowed man-made objects in real and simulated imagery.
Simulation of synthetic aperture radar (SAR) imagery may be approached in many different ways. One method treats a
scene as a radar cross section (RCS) map and simply evaluates the radar equation, convolved with a system impulse
response to generate simulated SAR imagery. Another approach treats a scene as a series of primitive geometric shapes,
for which a closed form solution for the RCS exists (such as boxes, spheres and cylinders), and sums their contribution
at the antenna level by again solving the radar equation. We present a ray-tracing approach to SAR image simulation that
treats a scene as a series of arbitrarily shaped facetized objects, each facet potentially having a unique radio frequency
optical property and time-varying location and orientation. A particle based approach, as compared to a wave based
approach, presents a challenge for maintaining coherency of sampled scene points between pulses that allows the
reconstruction of an exploitable image from the modeled complex phase history. We present a series of spatial sampling
techniques and their relative success at producing accurate phase history data for simulations of spotlight, stripmap and
SAR-GMTI collection scenarios.
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