摘要
传统的意图分析方法面临部分方法仅针对单个目标进行静态分析,以及精确推理耗费计算量过大的问题。针对上述问题,提出了一种新的基于动态贝叶斯网络的意图分析算法。该算法以群目标为对象,综合己方意图、交火程度、相对实力和相对速度等多种因素构建动态贝叶斯网络,并根据马尔可夫性实现快速近似推理,进一步通过融合估计得到对方的行动意图。仿真结果表明,该算法对复杂战场环境下群目标的行动意图能够实现动态可靠的评估,辅助支撑作战决策。
Traditional Intention Analysis（ IA） methods are confronted with the problems that most of them only focus on the static analysis of a single target and exact inference brings too much computational burden.For this reason,a novel Dynamic Bayesian Network（ DBN） based IA algorithm is proposed.In the proposed algorithm,firstly,DBN is constructed with various factors,i.e.,our intention,firefight,relative strength and relative velocity,for the IA of group targets.Then,the fast approximate inference is implemented according to Markov property.Finally,the analysis result of intention is obtained by fusion.Simulation results show that the proposed algorithm can reliably and dynamically evaluate the intention of group targets in complex battlefield environment.
出处
《无线电工程》
2017年第11期41-44,78,共5页
Radio Engineering
基金
海洋公益性科研专项基金资助项目(201505002)
关键词
意图分析
动态贝叶斯网络
近似推理
intention analysis
dynamic Bayesian network
approximate reasoning
