威胁联网环境下的无人机突防路径决策  

Path Decision-Making for Penetration of UAVs in Threat-Networked Environment

作　　者：张辉明[1] 鲁艺[1] 朱杰 ZHANG Hui-ming;LU Yi;ZHU Jie(Aeronautics and Astronautics Engineering Institute, Air Force Engineering University, Xi＇an 710038, China)

机构地区：[1]空军工程大学航空航天工程学院,西安710038

出　　处：《电光与控制》2018年第4期50-54,共5页Electronics Optics & Control

摘　　要：为了实现威胁联网环境下的无人机(UAV)突防路径决策,提出一种基于变结构离散动态贝叶斯网络(SVDDBN)的突防路径决策模型。根据无人机穿越探测威胁的方式和火力威胁的响应方式建立决策模型,运用基于自适应参数的变结构离散动态贝叶斯网络推理算法得到路径决策结果。仿真结果表明,该方法可以满足在威胁联网条件下的路径决策需求,为无人机突防提供了一种新思路。To catty out automatic path decision-making for the penetration of Unmanned Aerial Vehicles （UAVs） in threat-networked environment, a model for path decision-making is proposed based on Structure- Varied Discrete Dynamic Bayesian Network （SVDDBN）. The decision-making model is established according to the mode of UAV passing through the threat area and its response to firepower threat. Then the results of path decision-making are obtained by using the SVDDBN algorithm based on adaptive parameter. The results of simulation show that the model meets the need of path decision-making for UAVs in threat-networked environment and provides a new pattern of thinking for the penetration of UAVs.

关 键 词：无人机 低空突防 威胁联网 自适应参数 变结构离散动态贝叶斯网络 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]