基于模糊贝叶斯网的威胁等级评估研究  

Threat Level Assessment Based on Fuzzy Bayesian Networks

作　　者：丁达理[1,2] 罗建军[2] 王铀[1] 刘万俊[1] 

机构地区：[1]空军工程大学航空航天工程学院,西安710038 [2]西北工业大学航天学院,西安710072

出　　处：《电光与控制》2014年第9期7-10,15,共5页Electronics Optics & Control

基　　金：航空科学基金(20105196016)

摘　　要：针对现代复杂战场环境下威胁等级评估信息的不确定性,结合模糊数学及贝叶斯网提出了基于模糊贝叶斯网的威胁等级评估方法。在充分考虑威胁源相对于UCAV的距离、方位角对其隐身能力影响的基础上,从不确定性知识的概率化入手,综合天气、威胁类型、距离、方位角等不确定因素对威胁等级进行评估,采用加拿大Norsys软件公司的Netica软件建立贝叶斯网威胁评估模型并进行仿真。结果表明,该方法能快速、准确地评估威胁等级,具有一定的参考价值。Aiming at the uncertainty of Threat Level Assessment （TLA） data sources under moderncomplex battlefield, a fuzzy Bayesian network TLA method was proposed by integrating the fuzzy set theoryinto Bayesian networks. After well considering about the effect of the distance and azimuth angle of threatsources relative to a UCAV on its stealth capability, the threat level was evaluated by integrating suchuncertain factors as weather, threat type, distance and azimuth angle based on randomization of uncercainknowledge. Then a TLA Bayesian network was established by adopting Netica software of the Norsys SoftwareCompany in Canada, and simulation was carried out. The simulation results show that the method can assessthe threat level rapidly and accurately.

关 键 词：自主攻击 威胁等级评估 隐身能力 模糊理论 贝叶斯网 

分 类 号：V279[航空宇航科学与技术—飞行器设计]