北京航空航天大学学报 ›› 2020, Vol. 46 ›› Issue (6): 1097-1107.doi: 10.13700/j.bh.1001-5965.2019.0399

• 论文 • 上一篇    下一篇

基于CIDBN的战术活动识别模型及在线精确推理

国海峰1, 刘宏强1, 荘炎龙2, 杨海燕3   

  1. 1. 空军航空大学 航空作战勤务学院, 长春 130000;
    2. 空军航空大学 初级训练基地, 长春 130000;
    3. 空军工程大学 空管领航学院, 西安 710038
  • 收稿日期:2019-07-19 发布日期:2020-07-02
  • 通讯作者: 国海峰 E-mail:guohaifeng_hkd@sina.com
  • 作者简介:国海峰 男,博士,讲师。主要研究方向:无人飞行器作战系统与技术;刘宏强 男,博士,讲师。主要研究方向:航空作战指挥与智能决策;荘炎龙 男,助理工程师。主要研究方向:航空兵器可靠性评估;杨海燕 女,博士,副教授。主要研究方向:空天战场态势感知与威胁评估。
  • 基金资助:
    国家自然科学基金(61472441);装备预研领域基金(61403110304)

Tactical activity recognition model and online accurate inference based on CIDBN

GUO Haifeng1, LIU Hongqiang1, ZHUANG Yanlong2, YANG Haiyan3   

  1. 1. College of Aeronautical Operational Services, Air Force Aviation University, Changchun 130000, China;
    2. Junior Training Base of Air Force Aviation University, Changchun 130000, China;
    3. College of Air Control and Navigation, Air Force Engineering University, Xi'an 710038, China
  • Received:2019-07-19 Published:2020-07-02
  • Supported by:
    National Natural Science Foundation of China (61472441); China Equipment Pre-research Field Foundation (61403110304)

摘要: 战术活动识别是战场态势感知的重要研究内容。为提高战术活动识别的准确性与实时性,提出了一种基于上下文独立动态贝叶斯网络(CIDBN)的战术活动识别模型及在线精确推理。通过对战术活动机制的分析,采用动态贝叶斯网络(DBN)理论,建立了一个初始战术活动识别模型。该模型引入了威胁指数节点来影响战术活动的终止与选择,并采用模糊隶属度函数对连续变量进行离散化处理。依据上下文独立关系对该模型进行简化,获得了一个基于CIDBN的战术活动识别模型。将接口算法扩展于该模型上,提出了在线精确推理算法。仿真结果表明,所提出的战术活动识别方法,具有识别精度高、较低不确定性和实时性高的优点。

关键词: 动态贝叶斯网络(DBN), 接口算法, 上下文独立, 威胁指数, 精确推理

Abstract: Tactical activity recognition is an important research content of battlefield situational awareness. In order to improve the accuracy and real-time of tactical activity recognition, a tactical activity recognition model and online accurate reasoning based on Context-Independent Dynamic Bayesian Network (CIDBN) are put forward. Based on the analysis of tactical activity mechanism and Dynamic Bayesian Network (DBN) theory, an initial tactical activity recognition model is established. In this model, threat index nodes are introduced to influence the termination and selection of activities, and the fuzzy membership function is used to discretize the continuous variables. The model is simplified based on the relationship of context independence, and the new tactical activity recognition model based on CIDBN is obtained. The interface algorithm is extended to the model and an online accurate reasoning algorithm is proposed. The simulation results show that the proposed tactical activity recognition method has the advantages of high recognition accuracy, low uncertainty and high real-time performance.

Key words: Dynamic Bayesian Network (DBN), interface algorithms, context independence, threat index, exact inference

中图分类号: 


版权所有 © 《北京航空航天大学学报》编辑部
通讯地址:北京市海淀区学院路37号 北京航空航天大学学报编辑部 邮编:100191 E-mail:jbuaa@buaa.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发