This study introduces novel algorithms and the underlying mathematics to process photographs of planetary illuminated bodies and use them for navigation purposes. The goal is to accurately estimate the observer-to-body relative position in inertial coordinates. The main motivation is to provide autonomous navigation capabilities to spacecrafts by observing a planet or a moon. This is needed, for example, in human-rated vehicles in order to provide navigation capabilities in a loss-of-communications scenario. The algorithm is derived for the general case of a triaxial ellipsoid that is observed bounded by an elliptical cone. The orientation of the elliptical cone reference frame is obtained by eigenanalysis, and the offset between the elliptical cone axis and the body center direction as well as the equation of the terminator are quantified. The main contribution of this paper is in the image-processing approach adopted to derive centroid and distance to the body. This is done by selecting a set of pixels around the body limb and modeling the smooth limb transition using two-dimensional circular and elliptical sigmoid functions. More accurate estimates of the centroid and distance are then obtained by iterative nonlinear least-squares using these models. A sensitivity analysis is performed, and numerical examples using a real moon photograph taken from Earth are provided to clarify the image-processing steps and to validate the proposed theory.
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