A Review of Sensor Data Fusion for Explosives and Weapons Detection

The combination or fusion of data from multiple complementary sensors can potentially improve system performance in many explosives and weapons detection applications. The motivations for fusion can include improved probability of detection; reduced false alarms; detection of an increased range of threats; higher throughput and better resilience to adversary countermeasures. This paper presents the conclusions of a study which surveyed a wide range of data fusion techniques and examples of the research, development and practical use of fusion in explosives detection. Different applications types such as aviation checkpoint, checked baggage and stand-off detection are compared and contrasted, and the degree to which sensors can be regarded as 'orthogonal' is explored. Whilst data fusion is frequently cited as an opportunity, there are fewer examples of its operational deployment. Blockers to the wider use of data fusion include the difficulty of predicting the performance gains that are likely to be achieved in practice, as well as a number of cost, commercial, integration, test and evaluation issues. The paper makes a number of recommendations for future research work.