Cross Layers Decision Making and Fusion Model in Layered Sensing Systems

Layered sensing systems involve operation of several layers of sensing with different capabilities integrated into one whole system. The integrated layers of sensing must share information and local decisions across layers for better situation awareness. This research focused on the development of a model for decision making and fusion at the information level in layered sensing systems using the cloud model for uncertainty processing. In this research, the addition of a new processing level to the Joint Directors of Laboratories (JDL) processing model is proposed. The new processing level is called "Information Assessment, Fusion, and Control (IAFC)". Through this level, the different layers of a layered sensing system evaluate information about a given situation in terms of threat level and make a decision. The information assessment and control processing module was able to assess the threat level of a situation accurately and exchange assessments in order to determine the overall situation's threat level among all layers. The uncertain decisions were fused together to a unified decision using the cloud model of uncertainty processing methodology. Using this methodology, a cognitive element was added to the process of information assessment module leading to more accurate situation awareness.