|本期目录/Table of Contents|

[1]张健,罗鑫悦,黎宗孝,等.基于动态贝叶斯网络的无人机航迹模型研究*[J].中国安全生产科学技术,2023,19(11):188-193.[doi:10.11731/j.issn.1673-193x.2023.11.026]
　ZHANG Jian,LUO Xinyue,LI Zongxiao,et al.Research on UAV track model based on dynamic Bayesian network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(11):188-193.[doi:10.11731/j.issn.1673-193x.2023.11.026]
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基于动态贝叶斯网络的无人机航迹模型研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
19
期数:
2023年11期
页码:
188-193
栏目:
职业安全卫生管理与技术
出版日期:
2023-11-30

文章信息/Info

Title:
Research on UAV track model based on dynamic Bayesian network
文章编号:
1673-193X(2023)-11-0188-06
作者:
张健; 罗鑫悦; 黎宗孝; 赵嶷飞
（中国民航大学 空中交通管理学院，天津 300300）
Author(s):
ZHANG Jian;  LUO Xinyue;  LI Zongxiao;  ZHAO Yifei
(College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)
关键词:
无人机; 航迹预测; 动态贝叶斯网络; 航迹生成模型
Keywords:
unmanned aerial vehicle (UAV);  track prediction;  dynamic Bayesian network (BN);  track generation model
分类号:
X949
DOI:
10.11731/j.issn.1673-193x.2023.11.026
文献标志码:
A
摘要:
为了实现无人机自主冲突探测与解脱，解决航迹预测问题，采用动态贝叶斯网络，构建城市物流无人机航迹模型。通过借鉴经验模型搭建航迹数据变量间因果关系，形成初始贝叶斯网络和动态贝叶斯网络；然后对各变量进行初始化、离散化处理，应用历史数据进行模型训练，生成各子节点变量条件概率矩阵，依照条件概率矩阵动态预测离散值，并对其逆向连续化，并应用运动学方程，将预测航迹数据可视化。研究结果表明：基于无人机航迹模型，结合历史数据进行训练，可以实现无人机航迹生成和预测。研究结果可为无人机冲突探测与解脱算法研究提供参考。
Abstract:
In order to realize autonomous UAV conflict detection and resolution,UAV track prediction should be solved.A dynamic Bayesian network is selected to construct the track model of urban logistics UAV.The causal relationship between multiple variables of the track data is established by using the empirical model,and the initial Bayesian network and dynamic Bayesian network are formed.Each variable,such as UAV height,speed,acceleration,lifting rate and turning rate,is initialized and discretized.Then,according to the Bayesian network,the conditional probability matrix of each child node is generated by using the historical data for training.According to the conditional probability table of the Bayesian network variables,the piecewise quantized data of the acceleration,rise and fall rate and turn rate at the next moment are dynamically generated,and the discrete predicted values of the track variables are reverse-continuous processing and the kinematic equation is applied to visualize the generated track point data.The result of research shows that UAV track generation and prediction can be realized,based on the model and historical track data.The result of research provides reference for the UAV conflict detection and resolution algorithm research.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期： 2023-08-09
* 基金项目： 国家重点研发计划项目（2022YFB4300904）;天津市科技计划项目（21JCZDJC00780）;民航飞联网重点实验室开放基金项目(MHFLW202206)
作者简介： 张健，博士研究生，讲师，主要研究方向为空中交通管理、空域融合运行安全评估、无人机运行安全评估。
更新日期/Last Update: 2023-12-06