Abstract: In view of the event detection in situation assessment relies on domain knowledge, propose a method of situation assessment based on Rough-Vague set and D-S evidence theory. According to historical data of the target, establish a decision table. Through attribute reduction, generate a reduction event decision table, propose a method for obtaining Vague Set of the target event based on reduction decision table. According to the similarity of Vague sets, establish the evaluation coefficient to determine the outcome of events. The events which the target generate at different time is evidence, get the results of situation assessment based on the evidence combination formula. An example shows that the process of event detection doesn’t need to any domain knowledge, the method has a strongly focus ability to the uncertainty of the result for situation.

Key words: information fusion, situation assessment, Rough sets, Vague sets, D-S evidential theory

摘要： 针对态势估计中的事件检测需要依靠领域知识，提出一种基于Rough-Vague集与D-S证据理论的态势估计方法。基于Rough集与Vague集进行事件检测，根据目标历史数据建立事件决策表，通过属性约简得到简约的事件决策表，提出一种基于简约决策表获得目标事件Vague集的方法，根据Vague集的相似度建立评价系数来判定事件结果。目标在不同时刻发生的事件就是证据，基于证据合成公式得到最终的目标态势估计结果。实例分析表明该态势估计方法中事件检测不需要任何领域知识，对态势结果的不确定性具有很强的聚焦能力。

关键词: 信息融合, 态势估计, Rough集, Vague集, D-S证据理论