摘要
针对传感器测量数据的不确定性,提出基于模糊贝叶斯网络的态势威胁评估模型。该模型首先将不确定性数据分为模糊域和概率域两大类,然后在模糊域使用模糊综合评判得到威胁目标的动态威胁度,接着运用可能性概率转换理论将模糊表示的动态威胁度转化成概率域知识,最后在概率知识域使用贝叶斯网络推理算法得到目标的威胁等级。实例计算表明,该方法能够较好的反映威胁源的威胁等级,为武器系统选择跟踪打击目标提供决策依据,具有一定的实用性。
To process uncertain data obtained in sensors, a model of Situation and Threat Assessment （STA） based on fuzzy Bayesian network was proposed. The uncertain sensor data were divided into vagueness domain and probability domain. The vague data type of the threat target was handled by fuzzy comprehensive evaluation, and the dynamic threat degree was obtained in fuzzy domain. And then the fuzzy dynamic threat degree was translated into the probabilistic type by the possibility/probability theory. All the uncertain data were figured in probabilistic type and processed by Bayesian network to produce the threat level of the target. An example indicates that the fuzzy Bayesian network can obtain the real threat levels and is feasible for weapon system to automate decision-making on target-selecting and target-striking.
出处
《光电工程》
CAS
CSCD
北大核心
2008年第5期1-5,共5页
Opto-Electronic Engineering
基金
国防武器装备预研项目
关键词
态势评估
威胁评估
模糊综合评判
贝叶斯网络
situation assessment
threat assessment
fuzzy comprehensive evaluation
Bayesian network
