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针对目前战场态势变化的复杂性和多样性,尤其是战场信息的不确定性和模糊性,提出了利用动态贝叶斯网络,根据态势事件与态势假设之间的潜在关系建立态势评估的功能模型,从而实现态势评估,并用具体的实例验证了该方法的有效性.仿真结果表明,依据动态贝叶斯网络建立的态势评估模型,能够将各种特征因素进行综合,使得不同时间片的特征因素相互修正,从而能够准确地跟踪战场态势的变化,所得态势评估结果为指挥员分析当前态势和决策提供了支持.
Aiming at the complexity and diversity of battlefield situation changes, especially the uncertainty and fuzziness of battlefield information, this paper proposes a functional model of situation assessment based on the potential relationship between situation events and situational assumptions using dynamic Bayesian networks , So that the situation assessment can be realized and the effectiveness of this method is verified by a concrete example.The simulation results show that based on the situation assessment model established by the dynamic Bayesian network, various characteristic factors can be integrated so that the characteristic factors of different time slices So as to accurately track changes in the battlefield situation. The resulting assessment of the situation provides support to the commanders in analyzing the current situation and making decisions.