Generalized two-sided linear prediction approach for land mine detection

Ground penetrating radar (GPR) is a widely used sensor for land mine detection. However, GPR signal return is very susceptible to ground bounce and reflection of clutter objects, which makes the detection a difficult problem to date. In this paper, we propose to utilize two-sided linear prediction (LP) to model the background interference and then employ the residue energy to generate the test statistic. It is demonstrated from real GPR data that the proposed scheme is able to significantly suppress the interference due to ground reflection and is superior to the adaptive ground bounce removal and one-sided LP methods.