Multi-stage data fusion and the MSTWG TNO datasets

Data fusion is a branch of applied science that processes measurements from a variety of sources and time epochs to provide a consolidated state history of a reality of interest, be it a physical process, an intangible system (e.g. economic, social, ...), or a complex entity that includes elements of both (e.g. a set of individuals in physical space). As such, data fusion is an important component in military and security surveillance systems. The technology encompasses stochastic modeling, nonlinear filtering, data correlation, and sensor management. Thus, there are significant technical overlaps with the signal processing, automatic control, information theory, and operations research communities. This paper provides illustrations of some applications of data fusion technology to surveillance systems. The unifying theme of the examples is the use of innovative and flexible multi-stage fusion processing. Additionally, we explore the use of multi-stage processing in the context of some of the datasets from the multistatic tracking working group (MSTWG), and we describe recent work on performance evaluation of tracking systems.