In previous papers, we reported on the high-resolution ground-penetrating radar system designed, built, and deployed by SRI under contract to the Night Vision and Electronic Sensors Directorate at Fort Belvoir. Here, we report on some of the latest test results from the field demonstrations performed at government test sites, carefully designed to produce statistically significant results by employing many samples of a few representative metal and plastic mine types, buried at several depths. Significant improvements in performance above the baseline have been realized by using a number of statistically optimal image processing algorithms based on sound mathematical principles and techniques, guided by electromagnetic models of both mines and clutter. Principal component analysis was employed to define empirical models of buried mines using the polarimetric, complex data. A detector based on the generalized likelihood ratio test was then used on each image. Finally, multilook processing combined the results from several independent views of the same mines (at various ranges). For buried metal mines, at a probability of detection of 94%, the probability of false alarm per m2 decreased by an average factor of about four orders of magnitude over the baseline.