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In general, 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. However, radioactive target detection techniques usually do not differentiate between metal and oxide. In this study, data fusion techniques are applied to combine results from both the radiation detection and the electromagnetic induction (EMI) detection, so that further differentiation among DU metal, DU oxide, and non-DU metal debris may be achieved. A two-step approach is developed to accomplish decision level fusion. The approach is based on techniques such as majority voting (MV) and weighted majority voting (WMV), in combination with a set of decision rules. The fusion approach has been tested successfully with survey data collected on simulation targets.