In this study, we provide an extensive comparison of different clutter suppression techniques that are proposed to enhance ground penetrating radar (GPR) data. Unlike previous studies, we directly measure and present the effect of these preprocessing algorithms on the detection performance. Basic linear prediction algorithm is selected as the detection scheme and it is applied to real GPR data after applying each of the available clutter suppression techniques. All methods are tested on an extensive data set of different surrogate mines and other objects that are commonly encountered under the ground. Among several algorithms, singular value decomposition based clutter suppression stands out with its superior performance and low computational cost, which makes it practical to use in real-time applications.