Two new features are presented to improve the detection of Anti-Tank (AT) landmines using Ground Penetrating Radar (GPR). A simplified three dimensial physics based model is used as the basis for the features. We combine these features with the results of an algorithm known as LMS. We present promising feature detection algorithms known as Rings N' Things (RNT) and Cross Diagonal Enhancement Processing (CDEP) and our approach to combining the new features with the LMS features using logistic regression techniques. Test results from data gathered at multiple sites covering hundreds of mines and thousands of square meters is analyzed and presented.