基于模糊灰色认知图的复杂战场智能态势感知建模方法

针对复杂战场环境的动态、不确定性特征，提出一种基于模糊灰色认知图（FGCM）的智能态势感知（SA）建模方法。基于SA理论，采用自上而下任务驱动的态势觉察方式实现态势元素的提取；以目标威胁评估为态势理解的建模对象，利用FGCM在不确定数据表达和推理的模型特性，同时引入外部环境控制节点建立威胁评估动态FGCM模型。以目标意图预测为态势预测的建模对象，在基于专家知识建立的FGCM模型结构基础上，采用粒子群优化算法提高了意图预测模型对历史数据样本的参数学习能力。仿真验证分析结果表明，基于FGCM的智能SA建模方法能够较好地应对动态、不确定的战场环境，发挥知识和数据在建模中的综合作用。

FGCM-based Modeling Method of Intelligent Situation Awareness in Complex Battlefield

An intelligent situation awareness modeling method based on fuzzy grey cognitive map (FGCM) is proposed the dynamic and uncertain characteristics of complex battlefield environment. Based on situation awareness theory，the situation elements are extracted by top-down task driven situation awareness method. The target threat assessment is taken as the modeling object of situation understanding， and the dynamic FGCM model of threat assessment is established by using the model characteristics of FGCM in uncertain data expression and reasoning，in which the external environment control node is introduced. The target intention prediction is taken as the modeling object of situation prediction on the basis of FGCM model structure established based on expert knowledge， and the particle swarm optimization is used to improve the parameter learning ability of intention prediction model for historical data samples. The simulated results show that the intelligent situation awareness modeling method based on FGCM can deal with the dynamic and uncertain battlefield environment better，and play a comprehensive role of knowledge and data in modeling.