Fusion Techniques for Hybrid Ground Penetrating Radar - Electromagnetic Induction Landmine Detection Systems

Hybrid ground penetrating radar (GPR) and electromagnetic induction (EMI) sensors have advanced landmine detection far beyond the capabilities of a single sensing modality. Both probability of detection (PD) and false alarm rate (FAR) are impacted by the algorithms utilized by each sensing mode and the manner in which the information is fused. Algorithm development and fusion will be discussed, with an aim at achieving a threshold probability of detection (PD) of 0.98 with a low false alarm rate (FAR) of less than 1 false alarm per 2 square meters. Stochastic evaluation of pre-screeners and classifiers is presented with subdivisions determined based on mine type, metal content, and depth. Training and testing of an optimal prescreener on lanes that contain mostly low metal anti-personnel mines is presented. Several fusion operators for pre-screeners and classifiers, including confidence map multiplication, will be investigated and discussed for integration into the algorithm architecture.