系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (11): 3403-3412.doi: 10.12305/j.issn.1001-506X.2022.11.15
乔殿峰1, 梁彦1,*, 马超雄1, 杨心语1, 汪冕1, 李建国2
收稿日期:
2021-07-21
出版日期:
2022-10-26
发布日期:
2022-10-29
通讯作者:
梁彦
作者简介:
乔殿峰(1990-),男,博士研究生,主要研究方向为多源信息融合、目标识别、意图识别与预测跟踪|梁彦(1971-),男,教授,博士,主要研究方向为估计理论、信息融合、目标跟踪|马超雄(1995—), 男, 博士研究生, 主要研究方向为体系分析、复杂网络|杨心语(1997—), 女, 硕士研究生, 主要研究方向为目标跟踪、信息融合|汪冕(1997—), 男, 硕士研究生, 主要研究方向为信息融合、强化学习|李建国(1984—), 男, 副研究员, 博士, 主要研究方向为态势分析、意图推理
基金资助:
Dianfeng QIAO1, Yan LIANG1,*, Chaoxiong MA1, Xinyu YANG1, Mian WANG1, Jianguo LI2
Received:
2021-07-21
Online:
2022-10-26
Published:
2022-10-29
Contact:
Yan LIANG
摘要:
多域作战具有实体多类、队形多变、意图多样等诸多挑战,难以综合利用多元知识,因而主要依靠人工判决,以至于自动化水平不高。为了实现计算机自动推演态势,需要解决知识的图形化建模和意图推理综合两大难题。对此,在空海域管控知识图谱的基础上,搭建了多域作战战术规则库、编队队形与场景态势的映射关系,提出了基于多实体分层贝叶斯网络的群目标意图识别与预测方法。首先,运用群内目标实体的状态和事件信息,构建目标作战实体行为推理层。其次,利用综合作战实体的时序规则、双方相对距离及航向等信息,构建同类目标元意图推理层。最后,利用实体序列协作关系及编队队形信息,构建多域作战下的群目标总意图推理层。以航母群活动仿真数据为例,验证了所提算法能够获得较为可靠的意图推理结果。
中图分类号:
乔殿峰, 梁彦, 马超雄, 杨心语, 汪冕, 李建国. 多域作战下的群目标意图识别与预测[J]. 系统工程与电子技术, 2022, 44(11): 3403-3412.
Dianfeng QIAO, Yan LIANG, Chaoxiong MA, Xinyu YANG, Mian WANG, Jianguo LI. Recognition and prediction of group target intention in multi-domain operations[J]. Systems Engineering and Electronics, 2022, 44(11): 3403-3412.
表4
预警机状态-元意图关系表"
元意图 | 高度 | 速度 | 电磁信号 | 雷达状态 | 航向 | 敌我距离 | 干扰信号 | 是否投弹 |
起飞 | [0.01, 0.3, 0.59] | [0.1, 0.3, 0.6] | [0.1, 0.9] | [0.1, 0.9] | [0.9, 0.1] | [0.01, 0.29, 0.7] | [0.1, 0.9] | [0.05, 0.95] |
巡航 | [0.7, 0.29, 0.01] | [0.7, 0.29, 0.01] | [0.65, 0.35] | [0.65, 0.35] | [0.75, 0.25] | [0.55, 0.4, 0.05] | [0.65, 0.35] | [0.75, 0.25] |
归队 | [0.2, 0.45, 0.35] | [0.2, 0.5, 0.3] | [0.9, 0.1] | [0.8, 0.2] | [0.05, 0.95] | [0.15, 0.55, 0.3] | [0.1, 0.9] | [0.1, 0.9] |
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