A novel adaptive pre screener for ground penetrating radar
This paper describes a novel pre-screener algorithm for landmine detection with a ground penetrating radar (GPR). The pre-screener algorithms are used for finding anomalies that are potential locations of interest. Thus, their processing time is as important as their true detection rate and false alarm rate. The proposed approach is based on Kernel Least Mean Square algorithm. Although Least Mean Square (LMS) based approach has already been used in the literature, KLMS based approach is a novel application for landmine detection with GPR. In this study, KLMS approach is compared with LMS approach in terms of processing time, false alarm rate, and true detection rate.