A hierarchical distributed situation assessment model based on Bayesian networks
Jing Nong, Lei Wang, Huilin Yin · 2010
Situation assessment (SA) is one of the important processes in military decision. As a component of battlefield data fusion and decision support, SA is not easy to be realized ideally by using one particular technology in practice. Like any other complex military process, it requires the cooperation of lots of information processing technology. This paper describe a mechanism for constructing probabilistic models to represent and analyze uncertainties and assessing battlefield state based on a hierarchical distributed fusion processing of incoming information which can help commanders and analysts to model and assess the dynamic evolving situational state easily. We adopted a hierarchy distributed DBN model which can process information hierarchically and cooperatively through higher-level dynamic Bayesian networks and distributed lower-level dynamic Bayesian networks. And a 3-layer distributed computation environment is also introduced. The hierarchy distributed DBN can generate an accurate and efficient assessment of the battlespace and suitable for military hierarchical organizations.