A Method Of Situation Assessment Based On Bayesian Network And Ontology

Information fusion is a hot issue in the field of the military, the informationfusion technology includes multiple levels: low level fusion performs as estimatingthe position and attribute of the target, while high level fusion behaves to reckonongoing situation and threats of the battlefield. Therefore, the situation assessment isbased on the information of military targets and environment getting from first levelfusion, and confirms who is favored between enemy and us. During the process ofsituation assessment, many multiple-sourced, diversified format, and uncertainknowledge needs to be integrated. And then the prediction of situation can bereasoned from above. So, how to indicate and reason the uncertain knowledge aboutsituation is a significant problem to research. This paper is grounded on the×××assessment technology and the project×××battlefield information fusion system totake research on the two aspects, and main research work and achievements are asfollows:First, the paper describes situation assessment from definition, main concept,functional model, procedure of information, the way to express knowledge, method ofuncertainty reasoning and so on. All above provides a theory basis and actualapplication direction for the research for knowledge representation and reasoning inthe situation assessment.Secondly, on the basis of the theory of Bayesian network construction, learningand reasoning, the paper analyzes the basic procedure, main thoughts and applieddirection of Bayesian network in the application of situation assessment. According tothe process of situation assessment before, structure and probability of node inBayesian network are determined by experts’knowledge, which brings out certaindeviation between data and practice. As a result, the network is unsuited to dynamicbattlefield. So this paper puts forward the method of adaptive Bayesian network. Thismethod studies the training data from the low level fusion periodically, to get theBayesian network parameters reflecting the changes of the battlefield and to improvethe adaptability and accuracy of the situation assessment. At last the paper gives ahypothetical example, to proof that the adaptive Bayesian network is good at situationassessment.Thirdly, because of the mul-soruce and the variety format of the information inthe situation assessment, this paper introduces the theory of ontology. And construct situation assessment ontology for description of knowledge, to realize the knowledgesharing and reuse, and make the knowledge to be easy for automatic processing.However, as ontology has shortcomings of describing for uncertain knowledge, thispaper expands probability for the situation assessment ontology, and introduces asoftware framework which can convert situation assessment ontology into Bayesiannetwork. The experimental results show that the system framework is practical andfeasible, can provide an application framework for the subsequent research insituation assessment.Finally, this paper gives a software system which can realize the whole processof situation assessment. The system mainly includes: Scene emulation module,information fusion module, communication module, Bayesian network reasoningmodule, situation results displaying module. This system cleared the main process ofsituation assessment, and provides a basic application platform for the follow-upwork.