A survey of multi-sensor data fusion systems

Multi-sensor data fusion involves the integration of data from multiple sensors (and types of sensors) to perform inferences which are more accurate and specific than that available by processing single sensor data. Levels of inference range from target detection and identification to higher level situation assessment and threat assessment. In recent years, data fusion systems have been developed for a variety of applications including IFFN , C31, tactical resource management, and strategic warning as well as non-military applications. This paper provides a survey of more than 50 data fusion systems and summarizes their application, development environment, system status and indicates key techniques utilized. The techniques are mapped to a taxonomy previously developed by Hall and Linn (DFS-90 proceedings). These techniques include positional fusion techniques such as association and estimation, and identity fusion methods, including statistical methods, non-parametric methods, and cognitive based techniques (e.g. templating, knowledge-based systems, and fuzzy reasoning). An assessment of the state of fusion system development is provided.