中国科技核心期刊      中国指挥与控制学会会刊     军事装备类重点期刊
理论研究

无人机蜂群对海作战概念与关键技术研究

  • 钮伟 ,
  • 黄佳沁 ,
  • 缪礼锋
展开
  • 1. 中国航空工业集团公司雷华电子技术研究所, 江苏 无锡 214000
    2. 航空电子系统射频综合仿真航空科技重点实验室, 江苏 无锡 214000
钮伟(1991-),男,江苏宜兴人,硕士,工程师,研究方向为雷达资源管理,分布式人工智能。
黄佳沁(1990-),女,硕士。

收稿日期: 2017-12-04

  修回日期: 2017-12-20

  网络出版日期: 2022-05-14

版权

指挥控制与仿真编辑部, 2018, 版权所有,未经授权,不得转载、摘编本刊文章,不得使用本刊的版式设计。

Research on the Concept and Key Technologies of Unmanned Aerial Vehicle Swarm Concerning Naval Attack

  • NIU Wei ,
  • HUANG Jia-qin ,
  • MIAO Li-feng
Expand
  • 1. AVIC LEIHUA Electronic Technology Institute, Wuxi 214000
    2. Aviation Key Laboratory of Science and Technology on AISSS, Wuxi 214000, China

Received date: 2017-12-04

  Revised date: 2017-12-20

  Online published: 2022-05-14

Copyright

, 2018, Copyright reserved © 2018. Office of Acta Agronomica Sinica All articles published represent the opinions of the authors, and do not reflect the official policy of the Chinese Medical Association or the Editorial Board, unless this is clearly specified.

摘要

无人机蜂群作战是一种全新概念的作战模式,对未来战争的影响将是颠覆式的,随着研究的深入无人机集群作战正在从概念走向雏形。首先根据无人机蜂群的优势和海面目标的特性,提出了无人机蜂群对海作战的概念;随后,分析了国内外无人机蜂群的研究现状;总结了无人机蜂群作战的关键技术,包括:战术与作战使用、总体架构、集群感知与信息融合、集群控制与群体智能、任务规划和航迹规划等,并且详细论述了各项技术的重要性、难点以及解决方法,为将来的研究奠定了基础。

本文引用格式

钮伟 , 黄佳沁 , 缪礼锋 . 无人机蜂群对海作战概念与关键技术研究[J]. 指挥控制与仿真, 2018 , 40(1) : 20 -27 . DOI: 10.3969/j.issn.1673-3819.2018.01.004

Abstract

As an emerging and combat pattern, Unmanned Aerial Vehicle (UAV) swarm is exerting immeasurable influences on future wars day by day and reconstructing the inherent key technologies from its embryonic form of operation concepts. In this paper, the concept of UAV swarm on naval attacks is proposed first in the view of the advantages of UAV swarms and the features of sea-surface targets. Then, a review on the status quo is conducted succeeded by the summary of the key technologies on UAV swarm, in which the main swarm structure, swarm awareness and information fusion, swarm control and intelligence, mission and track planning are included. The key points, difficult points as well as the solutions with respects to respective technology are addressed in detail in order to lay the foundation for the future study.

参考文献

[1] Loc Pham. UVA swarm attack: protection system alternatives for destroyers[D]. Naval Postgraduate School, 2012.
[2] 杨王诗剑. 引领海战革命——浅析无人机“蜂群战术”[J]. 兵器知识, 2012(3):60-63.
[3] M Ownby. Mixed Initiative Control of Automa-teams (MICA)-a progress report[C]. AIAA the 3rd "Unmanned Unlimited" Technical Conference, Chicago, USA, 2004: 1-6.
[4] Jean-Charles Ledé. Collaborative Operations in Denied Environment (CODE) Program Overview[C]. Briefing Prepared for SPIE Defense + Security Symposium Sensors and Command, Control, Communications and Intelligence (C3I) Technologies for Homeland Security, Defense, and Law Enforcement Applications XV Conference, USA, 2016.
[5] DARPA. Gremlins[R].Tactical Technology Office, DARPA-BAA-15-59, 2015.
[6] Timothy H. Chung. Offensive Swarm-Enabled Tactics (OFFSET) [R]. DARPA, 2017.
[7] LOCUST: autonomous,swarming UAVs fly into the future [OL]. http://www.onr.navy.mil/Media-Center/PressRelea-ses/2015/LOCUST-low-cost-UAV-swarm-ONR.aspx,2015-04-14
[8] Schumacher C, Chandler P R, Rasmussen S J. Task Allocation for Wide Area Search Munitions via Iterative Network flow[C]. Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit. Monterey, California, 2002.
[9] Jaime E. Navy Unmanned Combat Air System Carrier Demonstration (UCAS-D) Overview [R]. USA, 2012.
[10] Ollero A, Lacroix S, Merino L, et al. Multiple Eyes in the Skies, Architecture and Perception Issues in the COMETS Unmanned Air Vehicles Project[J]. IEEE Robotics & Automation Magazine, 2005: 46-57.
[11] Franklin M. Unmanned Combat Air Vehicles: Opportunities for the Guided Weapons Industry[R]. Occasional Paper,Royal United Services Institute for Defense and Security Studies, 2008.
[12] 叶媛媛, 闵春平, 沈林成, 等. 基于满意决策的多UAV协同目标分配方法[J]. 国防科技大学学报, 2005,27(4):116-120.
[13] 谭何顺, 曹雷, 彭辉, 等. 一种多无人机层次化任务分配方法[J]. 解放军理工大学学报(自然科学版), 2014,15(1):18-24.
[14] 关震宇, 杨东晓, 李杰, 等. 基于Dubins路径的无人机避障规划算法[J]. 北京理工大学学报, 2014,34(6):570-576.
[15] 刘伟, 郑征, 蔡开元. 未知复杂环境中的无人机平滑飞行路径规划[J]. 控制理论与应用, 2012,29(11):1403-1413.
[16] 曲成刚, 曹喜滨, 张泽旭. 人工势场和虚拟领航者结合的多智能体编队[J]. 哈尔滨工业大学学报, 2014,46(5):1-5.
[17] 夏庆军, 张安, 张耀中. 大规模编队空战队形优化算法[J]. 控制理论与应用, 2010,27(10):1418-1423.
[18] TW McLain, RW Beard. Coordination variables, coordination functions, and cooperative timing missions[J]. AIAA Journal of Guidance Control & Dynamics, 2005,28(1):150-161.
[19] RW Beard, TW Mclain, DB Nelson, et al. Decentralized cooperative aerial surveillance using fixed-wing miniature UAVs[J]. Proceedings of the IEEE, 2006,94(7):1306-1324.
[20] Wei Y, Blakea M B, Madeya G R. An Operation-Time Simulation Framework for UAV Swarm Configuration and Mission Planning[J]. Procedia Computer Science, 2013,18(10):1949-1958.
[21] 袁利平, 陈宗基, 周锐, 等. 多无人机同时到达的分散化控制方法[J]. 航空学报, 2010(4):797-805.
[22] 彭辉, 沈林成, 朱华勇. 基于分布式模型预测控制的多UAV协同区域搜索[J]. 航空学报, 2010,31(3):593-602.
[23] Hayes-Roth B. Agents on Stage: Advancing the State of the Art of AI[R]. Knowledge Systems Laboratory, KSL-95-50, 1995.
[24] W Ren, RW Beard, TW Mclain. Coordination variables and consensus building in multiple vehicle systems[J]. Lecture Notes in Control & Information Science, 2005,309:439-442.
[25] W Ren, RW Beard. Consensus of information under dynamically changing interaction topologies[C]// IEEE American Control Conference, Boston, USA, 2004: 4939-4944.
[26] 韩健. 基于多Agent的无人机协作控制[D]. 哈尔滨:哈尔滨工业大学, 2012.
[27] 王强. UAV集群自主协同决策控制关键技术研究[D]. 西安:西北工业大学, 2015.
[28] 汪小帆, 李翔, 陈关荣. 复杂网络理论及其应用[M]. 北京: 清华大学出版社, 2006.
[29] YY Liu, JJ Slotine, A L Barabási. Controllability of complex networks[J]. Nature, 2011,473(7346):167-173.
[30] J Ruths, D Ruths. Control profiles of complex networks[J]. Science, 2014,343(6177):1373-1376.
[31] S Shen, Y Mulgaonkar, N Michael, et al. Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft MAV[C]// 2014 IEEE International Conference on Robotics and Automation(ICRA), Hong Kong, China, 2014: 4974-4981.
[32] G Abdi, F Samadzadegan, F Kurz. Pose estimation of unmanned aerial vehicles based on a vision-aided multi-sensor fusion[J]. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016, XLI-B6:193-199.
[33] 王林, 王楠, 朱华勇 等. 一种面向多无人机协同感知的分布式融合估计方法[J]. 控制与决策, 2010,25(6):814-820.
[34] 欧阳瑞斌. 无人机群通信技术研究[D]. 北京:北京理工大学, 2016.
[35] 刘昕. 军用无人机自组网技术研究[D]. 南京:南京理工大学, 2014.
[36] 韩崇昭, 朱洪艳, 段战胜, 等. 多源信息融合[M]. 北京: 清华大学出版社, 2006.
[37] 何友, 王国宏, 陆大金, 等. 多传感器信息融合及应用[M]. 北京: 电子工业出版社, 2000.
[38] 徐毅, 金德琨, 敬忠良. 数据融合研究的回顾与展望[J]. 信息与控制, 2002,31(3) : 250-255.
[39] 孟章荣. 军事应用中的多源信息融合技术[J]. 现代防御技术, 2001,29(2):27-30.
[40] Hall D L, Llinas J. Introduction to multisensory data fusion[C]. Proceedings of the IEEE, 1997,85(1):6-33.
[41] 吴荣春. 军事信息系统中信息融合关键技术研究[D]. 成都:电子科技大学, 2016.
[42] 梁晓龙, 孙强, 尹忠海, 等. 大规模无人系统集群智能控制方法综述[J]. 计算机应用方法研究, 2015(32):11-16.
[43] 程代展, 陈翰馥. 从群集到社会行为控制[J]. 科学导报, 2004(8):4-7.
[44] 肖人彬. 群集智能特性分析及其对复杂系统研究的意义[J]. 复杂系统与复杂性科学, 2006,3(3) : 10-19.
[45] KWONG H, JACOB C. Evolutionary exploration of dynamic swarm behavior[C]// Proc of IEEE Congress on Evolutionary Computation. 2003: 367-374.
[46] TANNER H G, JADBABAIE A, PAPPAS G J. Stable flocking of mobile agents,part Ⅱ: dynamic topology[C]// Proc of the 42nd IEEE Conference on Decision and Control. 2003: 2016-2021.
[47] S Kim, Y Kim, A Tsourdos. Optimized behavioural UAV formation flight controller design[C]// Proceedings of the European Control Conference, Budapest, Hungary, 2009: 4973-4978.
[48] J Shin, S Kim, J Suk. Development of robust flocking control law for multiple UAVs using behavioral decentralized method[J]. Journal of the Korean Society for Aeronautical and Space Sciences, 2015,43(10):859-867.
[49] HX Qiu, HB Duan, YM Fan. Multiple unmanned aerial vehicle autonomous formation based on the behavior mechanism in pigeon flocks[J]. Control Theory & Applications, 2015,32(10):1298-1304.
[50] COUZIN I D, KRAUSE J, FRANKS N R, et al. Effective leadership and decision-making in animal groups on the move[J]. Nature, 2005,433(7025) : 513-516.
[51] M Turpin, N Michael, V Kumar. Trajectory design and control for aggressive formation flight with quadrotors[J]. Autonomous Robots, 2012,33(1/2):143-156.
[52] M Saska, T Baca, J Thomas, et al. System for deployment of groups of unmanned micro aerial vehicles in GPS-denied environments using onboard visual relative localization[J]. Autonomous Robots, 2017,41(4):919-944.
[53] T Nageli, C Conte, A Domahidi, et al. Environment independent formation flight for micro aerial vehicles[C]// IEEE International Conference on Intelligent Robots and Systems, Chicago, USA, 2014: 1141-1146.
[54] AS Aghdam, MB Menhaj, F Barazandeh, et al. Cooperative load transport with movable load center of mass using multiple quadrotor UAVs[C]// 2016 4th International Conference on Control, Instrumentation, and Automation, Qazvin, Iran, 2016: 23-27.
[55] H Liu, XK Wang, HY Zhu. A novel back stepping method for the three-dimensional multi-UAVs formation control[C]// IEEE International Conference on Mechatronics and Automation, Beijing, China, 2015: 923-928.
[56] 俞辉, 王永骥. 基于动态拓扑有领航者的智能群体群集运动控制[J]. 系统工程与电子技术, 2006,28(11) : 1721-1724.
[57] GAZI V. Swarm aggregations using artificial potentials and sliding-mode control[J]. IEEE Trans on Robotics, 2005,21(6) : 1208-1214.
[58] X Liang, GL Meng, HT Luo, et al. Dynamic path planning based on improved boundary value problem for unmanned aerial vehicle[J]. Cluster Computing, 2016,19(4):2087-2096.
[59] F Liao, R Teo, JL Wang, et al. Distributed formation and reconfiguration control of VTOL UAVs[J]. IEEE Transactions on Control Systems Technology, 2017,25(1):270-277.
[60] 赵明, 苏小红, 马培军, 等. 复杂多约束 UAVs 协同目标分配的一种统一建模方法[J]. 自动化学报, 2012,38(12):2038-2048.
[61] Edison E, Shima T. Integrated task assignment and path optimization for cooperating uninhabited aerial vehicles using genetic algorithms[J]. Computers & Operations Research, 2011,38(1):340-356.
[62] Eun Y, Bang H. Cooperative task assignment/path planning of multiple unmanned aerial vehicles using genetic algorithms[J]. Journal of Aircraft, 2009,46(1):338-343.
[63] M Kothari, I Postlethwaite. A probabilistically robust path planning algorithm for UAVs using rapidly-exploring random trees[J]. Journal of Intelligent & Robotic Systems, 2013,71(2):231-253.
[64] H Shorakaei, M Vahdani, B Imani, et al. Optimal cooperative path planning of unmanned aerial vehicles by a parallel genetic algorithm[J]. Robotica, 2014,34(4):823-836.
[65] XY Zhang, HB Duan. An improved constrained differential evolution algorithm for unmanned aerial vehicle global route planning[J]. Applied Soft Computing, 2015,26(C):270-284.
[66] 李少斌, 陈炎财, 杨忠, 等. 具有通信延迟的多无人机编队飞行控制[J]. 信息与控制, 2012(2):142-146.
文章导航

/