Survey of multisensor data fusion systems

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Abstract
Multisensor data fusion integrates data from multiple sensors (and types of sensors) to perform inferences which are more accurate and specific than those from processing single-sensor data. Levels of inference range from target detection and identification to higher level situation assessment and threat assessment. This paper provides a survey of more than 50 data fusion systems and summarizes their application, development environment, system status and key techniques. The techniques are mapped to a taxonomy previously developed by Hall and Linn (1990); these include positional fusion techniques, such as association and estimation, and identity fusion methods, including statistical methods, nonparametric methods, and cognitive techniques (e.g. templating, knowledge-based systems, and fuzzy reasoning). An assessment of the state of fusion system development is provided.

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