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\paragraph{Introduction}  \setlength{\parindent}{10ex} \setlength{\parindent}  Radar is a powerful tool for gathering information about bodies in the Solar System. Radar allows for determination of orbital elements of both planets and minor bodies (such as asteroids and comets) to high precision. A relatively new use for radar has been computing asteroid shapes based on their radar signature. This problem is not trivial -- without information on the spin axis of the asteroid, the underlying shape of the body cannot be uniquely determined from its radar image. Furthermore, even if spin information were known, certain peculiarities of the radar images such as the North South ambiguity make recovery of the physical shape extremely difficult. The best method to accomplish this is by fitting a model for the physical shape to the observed radar image. Unfortnuately, this is a computationally intensive problem, potentially involving hundreds to thousands of free parameters, and millions of data points.\par  Given the computational intensity, one might raise the question as to the worth of computing shape information from radar data. The most compelling reason to do so is the fact that radar is not diffraction limited, since it does not require spatial resolution of the object. This means that radar can be used to resolve objects substantially smaller than the beamwidth of the detector used to obtain the images. For example, Arecibo, the primary instrument used for the data presented in this paper, has a beamwidth of more than an arcminute. Yet Arecibo can easily gather shape information to an accuracy of decameters for objects which subtend 20 milliarcseconds. \par  Radar has other advantages as well. Unlike most observational techniques inside the Solar System, radar does not rely on reflected sunlight. This human-controlled illumination allows for greater flexibility with respect to the observations. Radar also has the ability to probe an object's sub-surface properties, which can give important information about the object such as porosity, surface-ice content, and surface conductivity. \par