基于动态贝叶斯网络的低慢小目标威胁评估

LSS target threat evaluation based on dynamic Bayesian network

针对复杂地形下低慢小目标难以防御的难题,本文分析并研究对于与低慢小目标威胁评估具有影响作用的因素,提出一种基于动态贝叶斯网络的威胁评估方法。基于低慢小目标的威胁属性,构建动态贝叶斯网络拓扑,利用贝叶斯理论推理出威胁值;并通过仿真试验验证该种基于动态贝叶斯网络的方法在对低慢小目标进行威胁评估是可行的。

Aiming at the difficult problem oflow-slow-and-small(LSS)targets in complex terrain,this paper analyzes and studies the factors affecting the threat assessment of LSS targets to propose a threat assessment method based on dynamic Bayesian network.Based on the threat attribute of LSS targets,we construct a dynamic Bayesian network topology and deduce the threat value by Bayesian theory.Thesimulation results show that the method based on dynamic Bayesian network is feasible in threat assessment of LSS targets.