基于深度学习的空天防御态势感知方法
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摘要
空天防御态势感知是实现空天防御战场透明化,降低信息复杂度,提升空天防御作战指挥决策支撑能力的前提和基础。系统分析了未来空天防御战场态势感知面临的巨大威胁和挑战,提出了复杂信息对抗条件下态势信息数据挖掘、融合处理、意图预测的能力需求,在此基础上结合深度学习的特征提取能力,构建了基于深度学习理论的空天防御态势感知体系结构,最后探讨了关键技术,为未来空天防御态势感知技术的发展提供了新的思路。
Aerospace defense situation awareness is prerequisite and basis to make the aerospace defense battlefield more transparent,reduce complexity of information and improve the command and support capacity of aerospace defense operational commanding. This paperputs forward the demands of data mining, fusion processing, intention anticipation based on analyzing tremendous threats and challenges of aerospace defense situation awareness systematically. Then the structure of situation awareness based on deep learning is established. The key technologies in the structure at the end of the article expounded. This paperprovides a new idea forthe development of aerospace defense situational awareness.
Aerospace defense situation awareness is prerequisite and basis to make the aerospace defense battlefield more transparent,reduce complexity of information and improve the command and support capacity of aerospace defense operational commanding. This paperputs forward the demands of data mining, fusion processing, intention anticipation based on analyzing tremendous threats and challenges of aerospace defense situation awareness systematically. Then the structure of situation awareness based on deep learning is established. The key technologies in the structure at the end of the article expounded. This paperprovides a new idea forthe development of aerospace defense situational awareness.
引文
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[20]金欣.“深绿”及Alpha Go对指挥与控制智能化的启示[J].指挥与控制学报,2016,2(3):202-207.
[21]赵冬斌,邵坤,朱圆恒,等.深度强化学习综述:兼论计算机围棋的发展[J].控制理论与应用,2016,33(6):701-717.
[22]LITTMAN M L.Reinforcement learning improves behaviour from evaluative feedback[J].Nature,2015,521(7553):445-451.
[23]郭圣明,贺筱媛,胡晓峰,等.军用信息系统智能化的挑战与趋势[J].控制理论与应用,2016,33(12):1562-1570.
[24]MNIH V,KAVUKCUOGLU K,SILVER D,et al.Human-level control through deep reinforcement learning[J].Nature,2015,518:529-541.
[25]祁炜,李侠,蔡万勇,等.空袭中预警机阵位选择及航线规划[J].火力与指挥控制,2016,41(12):64-68.
[26]董龙明,高天成,邱瑞波,等.任务驱动一体化作战指挥信息系统高效协同技术[J].火力与指挥控制,2017,42(5):79-83.
[2]汪胜利.大数据时代指挥信息系统发展分析[J].现代雷达,2013(5):1-5.
[3]李小龙,李姝.大数据分析在指挥信息系统中的运用[C]//北京:第二届中国指挥控制大会论文集——网络时代的公共安全与应急救援,2014:872-876.
[4]郑书奎,吴琳,贺筱媛.基于深度学习的兵棋演习数据特征提取方法研究[J].指挥与控制学报,2016,2(3):194201.
[5]张彬超,寇雅楠,邬蒙,等.基于深度置信网络的近距空战态势评估[J].北京航空航天大学学报,2017,43(7):1450-1459.
[6]姚庆锴,柳少军,贺筱媛,等.战场目标作战意图识别问题研究与展望[J].指挥与控制学报,2017,3(2):127-131.
[7]ENDSLEY M R.Toward a theory of situation awareness in dynamic systems[J].Human Factors,1995,37(1):32-64.
[8]何榕,罗小明.探析美军C2BMC系统及对空天防御指挥控制系统建设的启示[J].兵工自动化,2016,35(9):1-4.
[9]张昌芳,朱启超,匡兴华.美国弹道导弹防御C2BMC系统发展综述[J].装备学院学报,2012,23(3):60-63.
[10]HAMILTON B A.A statement of operational needs on the operational concept and capabilities of the ballistic missile defense system,command and control,battle management and communications(C2BMC)Element[R].U.S.Strategic Command JFCC-IMD,2006.
[11]胡晓峰,贺筱媛,饶德虎.基于复杂网络的体系作战协同能力分析方法研究[J].复杂系统与复杂性科学,2015,12(2):9-17.
[12]贾珺,吴元立,贺筱媛,等.作战协同关系超图模型[J].国防科技大学学报,2015,37(3):185-190.
[13]雷锟,王劲松,阳名喜.大数据在信息作战指挥决策中的运用[J].指挥控制与仿真,2016,38(3):24-27.
[14]陶九阳,吴琳,胡晓峰.Alpha Go技术原理分析及人工智能军事应用展望[J].指挥与控制学报,2016,2(2):114-120.
[15]焦李成,杨淑媛,刘芳,等.神经网络七十年:回顾与展望[J].计算机学报,2016,39(8):1697-1716.
[16]ERHAN D,BENGIO Y,COURVILLE A,et al.Why does unsupervised pre-training help deep learning[J].Journal of Machine Learning Research,2010(11):625-660.
[17]孙志军,薛磊,许阳明,等.深度学习研究综述[J].计算机应用研究,2012,29(8):2806-2810.
[18]BENGIO Y.Learning deep architectures for AI[J].Foundations and Trends in Machine Learning,2009,2(1):1-127.
[19]SILVER D,HUANG A,MADDISON C J,et al.Mastering the game of Go with deep neural networks and tree search[J].Nature,2016,529(7587):484-489.
[20]金欣.“深绿”及Alpha Go对指挥与控制智能化的启示[J].指挥与控制学报,2016,2(3):202-207.
[21]赵冬斌,邵坤,朱圆恒,等.深度强化学习综述:兼论计算机围棋的发展[J].控制理论与应用,2016,33(6):701-717.
[22]LITTMAN M L.Reinforcement learning improves behaviour from evaluative feedback[J].Nature,2015,521(7553):445-451.
[23]郭圣明,贺筱媛,胡晓峰,等.军用信息系统智能化的挑战与趋势[J].控制理论与应用,2016,33(12):1562-1570.
[24]MNIH V,KAVUKCUOGLU K,SILVER D,et al.Human-level control through deep reinforcement learning[J].Nature,2015,518:529-541.
[25]祁炜,李侠,蔡万勇,等.空袭中预警机阵位选择及航线规划[J].火力与指挥控制,2016,41(12):64-68.
[26]董龙明,高天成,邱瑞波,等.任务驱动一体化作战指挥信息系统高效协同技术[J].火力与指挥控制,2017,42(5):79-83.