In this paper, we discuss approaches for processing ground penetrating radar (GPR) data for land mine detection. We discuss two methods of clutter suppression using ARMA modeling and also examine feature extraction using both ARMA modeling and complex natural resonance (CNR) modeling. The algorithms presented have been tested on laboratory GPR data and been found to be promising techniques. In future work, the feature vectors produced by these techniques will be processed through appropriate detection algorithms.