A method for detecting shallowly buried landmines using sequential ground penetrating radar (GPR) data is presented. After removing a dominant coherent component arising from the ground surface reflection from the GPR data, three kinds of target features related to wave correlation, energy ratio, and signal arrival time are extracted. Since the detection problem treated here is reduced to a binary hypothesis test, an approach based on a likelihood ratio test is employed as a detection algorithm. In order to check the detection performance, a Monte Carlo simulation is carried out for data generated by a two-dimensional finite-difference time domain (FDTD) method. Results given in the form of receiver operating characteristic (ROC) curves show that good detection performance is obtained even for landmines buried at shallow depths under rough ground surfaces, where the responses from the landmines and that from the ground surface overlap in time.