A characteristic of vehicle-based ground-penetrating radar is the hyperbolic signature generated by targets such as landmines. The hyperbola provides a significantly different shape from most false alarms. Here an approach is introduced that seeks to utilize all of the energy contained in this characteristic hyperbolic signature. We propose a Hyperbola Flattening Transform (HFT) that transforms hyperbolic signatures of interest into straight lines, which are in turn detected using the Radon transform. The algorithm is applied to both simulated and real data. Encouraging results are presented when applying the HFT to the problem of detecting low signal-to-noise ratio plastic mines.