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This thesis considers the use of synthetic aperture radar (SAR) to provide absolute platform position information in scenarios where GPS signals may be degraded, jammed, or spoofed. Two algorithms are presented, and both leverage known 3D ground structure in an area of interest, e.g. provided by LIDAR data, to provide georeferenced position information to airborne SAR platforms. The first approach is based on the wide-aperture layover properties of elevated reflectors, while the second approach is based on correlating backprojected imagery with digital elevation imagery. Both of these approaches constitute the system we have designated: SARNAV. Building on 3D backprojection, localization solutions result from non-convex optimization problems based on image sharpness or correlation measures. Results using measured GOTCHA data demonstrate localization errors of only a few meters with initial uncertainty regions as large as 16 km^2. Finally, the system is incorporated into a Kalman filter tracker, where periodic SARNAV updates could be used to correct drift from an inertial navigation system. With measured data, the system was able to track the true position along the route within a few meters of error.