基于人机智能融合技术的态势感知应用研究  

Application Research of Situation Awareness Based on Human-machine Intelligence Fusion Technology

作　　者：王海 潘越[1] 郭继光[1] 陆泽健[1] 于荣欢 WANG Hai;PAN Yue;GUO Ji-guang;LU Ze-jian;YU Rong-huan(China Academy of Electronics and Information Technology,Beijing 100041,China;Space Engineering University,Beijing 101416,China)

机构地区：[1]中国电子科学研究院,北京100041 [2]航天工程大学,北京101416

出　　处：《中国电子科学研究院学报》2023年第12期1100-1112,共13页Journal of China Academy of Electronics and Information Technology

基　　金：复杂电子系统仿真重点实验室基金资助项目(6142010062105)。

摘　　要：随着网络信息和人工智能技术的快速发展,态势感知(Situational Awareness,SA)正在由传统的以人为主转向人机智能融合发展阶段,构建人机融合的SA生态系统将成为未来战场胜负的重要决定因素。未来的SA是智能化的人、机、环境在各方面深度交互形成的人机融合新型“计算-算计”博弈系统。本文面向人机智能融合SA生态系统的建设,探讨了新型SA技术的概念、发展历程,提出人机智能融合SA体系架构和框架模型,构建了深度学习、强化学习、迁移学习人机融合技术的智能SA典型应用模型。最后,展望人机融合智慧技术面临的挑战,把握未来的发展趋势,对构建新型的SA生态系统提供参考借鉴。With the rapid development of network information and artificial intelligence technology,the situational awareness(SA)is shifting from the traditional human-oriented to the human-machine integrated fusion development stage,and the construction of human-machine integration SA ecosystem will become an important determinant of the future battlefield outcome.The future SA is a new“computational-calculative”game system of human-machine integration formed by the deep interaction of intelligent man,machine and environment in all aspects.Aiming at the construction of human-machine intelligence fusion SA ecosystem,this work discusses the concept and development history of new SA technology,proposes the architecture and framework model of human-machine intelligence fusion SA system,and constructs the typical application model of intelligent SA based on deep learning,reinforcement learning,and transfer learning.Finally,looking forward to the challenges faced by human-machine intelligence fusion technology,this paper grasps the future development trend,and provide some reference for building a new SA ecosystem.

关 键 词：态势感知 人机智能融合 人工智能 深度学习 强化学习 迁移学习 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TN97[自动化与计算机技术—控制科学与工程]