Decision fusion for buried radioactive target detection and discrimination using radiation and EMI data

Buried penetrators made of Depleted Uranium (DU) become hazardous waste. In addition to the detection of DU waste, it is also of interest to know their state of oxidation. Previously, a data fusion method was developed to differentiate between DU metal, DU oxide, and non-DU metal debris. The method combines results from both the radiation detection and the electromagnetic induction (EMI) detection, using a two-step fusion approach. In this paper, decision fusion is further applied to combine different detectors for improved radiation detection, so that the final results from radiation-EMI fusion may be more reliable. Experiments are conducted with survey data collected on simulation targets. The results show that the improved method helps reduce the false alarms significantly.