Evaluation Method for SoS Contribution Rate of All-optical UAV Swarm Based on ABMS

doi:10.12382/bgxb.2023.0830

Abstract

Abstract:

To study the operational concept of all-optical UAV swarm in unknown complex-terrain battlefield environment, an evaluation method is proposed. The method is used to evaluate the effectiveness and the system-of-systems (SoS) contribution rate of all-optical UAV swarm and is based on Agent-based modeling and simulation (ABMS). Firstly, the evaluation index system is established according to the combat characteristics of all-optical UAV swarm. Then, the modular agent model of each combat unit is given. Finally, the simulation of patrol and attack mission in ultra-low altitude is carried out. Analyzing the influences of all-optical UAV perception performance, all-optical UAV communication performance, swarm size and swarm configuration on swarm survival rate, tasks completion rate, battle damage rate and SoS contribution rate. The research results show that the all-optical UAV can bring new capabilities to the combat system and effectively improve the combat effectiveness of SoS. Results also show that a larger swarm size and a higher proportion of all-optical UAV can increase the combat effectiveness of SoS. And the contribution brought by the improvement of the performance of all-optical UAV is not significant.

Key words: UAV swarm, operational concept, Agent, combat modeling and simulation, effectiveness evaluation, SoS contribution rate

CLC Number:

V279

ZHANG Qi, GE Yuxue, LI Pan, KANG Qijun, PEI Yang. Evaluation Method for SoS Contribution Rate of All-optical UAV Swarm Based on ABMS[J]. Acta Armamentarii, 2023, 44(11): 3422-3435.

Figures/Tables 20

Fig.1 Evaluating process

Fig.2 Framework model of all-optical UAV agent

Fig.3 Evaluation index system of all-optical UAV

Fig.4 Demonstration of combat units and their relationship

Fig.5 Behaviour model of all-optical UAV agent

Fig.6 Schematic diagram of laser seeker

Fig.7 Flow chart of three-dimensional path planning algorithm

Fig.8 Three-dimensional terrain modelling

Fig.9 Demonstration of feasible region

Fig.10 Behaviour model of missile agent

Fig.11 Behaviour model of command center agent

Fig.12 Behaviour model of enemy targets agent

Fig.13 Interface of the simulation

Table 1 Parameters in the simulation

作战单元	参数	数值
全光化无人机集群	无人机总数量	50
	全光化无人机比例/%	50, 100
	感知距离/km	20
全光化无人机	识别确认概率	0.9
	通信距离/km	20
	相对高度限制/m	50~200
常规无人机	感知距离/km	10
	相对高度限制/m	50~200
	数量	7
敌方目标	干扰距离/km	20
	干扰强度	0.5

Fig.14 Analysis on the variation of index value with the number of experiments

Table 2 Design of the experiment

实验组号	全光化无人机感知距离/km	全光化无人机通信距离/km	集群无人机总数量	全光化无人机所占比例/%
1	10~30	20	50	0, 50, 100
2	20	10~30	50	0, 50, 100
3	20	20	10~60	0, 50, 100
4	20	20	50	0~100

Fig.15 Analysis on the influence of perception distance of all-optical UAV

Fig.16 Analysis on the influence of communication distance of all-optical UAV

Fig.17 Analysis on the influence of the number of UAV in swarm

Fig.18 Analysis on the influence of the proportion of all-optical UAV

References 32

[1]	毛军, 付浩, 褚超群, 等. 惯性/视觉/激光雷达SLAM技术综述[J]. 导航定位与授时, 2022, 9(4):17-30.
	MAO J, FU H, CHU C Q, et al. A review of simultaneous localization and mapping based on inertial-visual-lidar fusion[J]. Navigation Positioning and Timing, 2022, 9(4):17-30. (in Chinese)
[2]	潘时龙, 张亚梅. 微波光子雷达及关键技术[J]. 科技导报, 2017, 35(20):36-52.
	PAN S L, ZHANG Y M. Microwave photonic radar and key technologies[J]. Science & Technology Review, 2017, 35(20):36-52. (in Chinese)
[3]	郭光灿, 陈以鹏, 王琴. 量子计算机研究进展[J]. 南京邮电大学学报(自然科学版), 2020, 40(5):3-10.
	GUO G C, CHEN Y P, WANG Q. Advances in quantum computer research[J]. Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition), 2020, 40(5):3-10. (in Chinese)
[4]	王天枢, 林鹏, 董芳, 等. 空间激光通信技术发展现状及展望[J]. 中国工程科学, 2020, 22(3):92-99.
	WANG T S, LIN P, DONG F, et al. Progress and prospect of space laser communication technology[J]. Strategic Study of CAE, 2020, 22(3):92-99. (in Chinese) doi: 10.15302/J-SSCAE-2020.03.014 URL
[5]	杨克巍, 杨志伟, 谭跃进, 等. 面向体系贡献率的装备体系评估方法研究综述[J]. 系统工程与电子技术, 2019, 41(2):311-321.
	YANG K W, YANG Z W, TAN Y J, et al. Review of the evaluation methods of equipment system of systems facing the contribution rate[J]. Systems Engineering and Electronics, 2019, 41(2):311-321. (in Chinese) doi: 10.3969/j.issn.1001-506X.2019.02.13
[6]	TRAN H T, DOMERÇANT J C, MAVRIS D N. Evaluating the agility of adaptive command and control networks from a cyber complex adaptive systems perspective[J]. Journal of Defense Modeling and Simulation:Applications, Methodology, Technology, 2015, 12(4):405-422. doi: 10.1177/1548512915592517 URL
[7]	TIAN Y P, LIU H, HUANG J. Aircraft performance analysis in conceptual design phase based on system-of-systems simulations[J]. MATEC Web of Conferences, 2016, 52: 01001. doi: 10.1051/matecconf/20165201001 URL
[8]	刘文金, 裴扬, 葛玉雪, 等. 基于ABMS的对地攻击型无人机体系贡献率评估[J]. 航空学报, 2022, 43(9):225972. doi: 10.7527/S1000-6893.2021.25972
	LIU W J, PEI Y, GE Y X, et al. System-of-systems contribution evaluation method of ground-attack UCAV based on ABMS[J]. Acta Aeronautica et Astronautica Sinica, 2022, 43(9):225972. (in Chinese)
[9]	MASSEI M, TREMORI A. Simulation of an urban environment by using intelligent agents within asymmetric scenarios for assessing alternative command and control network-centric maturity models[J]. Journal of Defense Modeling and Simulation, 2014, 11(2):137-153. doi: 10.1177/1548512912466319 URL
[10]	MOUR A, KENLEY C R, DAVENDRALINGAM N, et al. Agent-based modeling for systems-of-systems[C]//Proceedings of the 2013 INCOSE International Symposium. Philadelphia:INCOSE, 2013:973-987.
[11]	张睿文, 宋笔锋, 裴扬, 等. 基于ABMS的飞机拦截作战效能评估方法[J]. 系统工程与电子技术, 2018, 40(2):322-329.
	ZHANG R W, SONG B F, PEI Y, et al. Evaluation method for operational effectiveness of aircraft interception based on ABMS[J]. Systems Engineering and Electronics, 2018, 40(2):322-329. (in Chinese)
[12]	PENG B, LIU S, XU L, et al. Combat process simulation and attrition forecasting based on system dynamics and multi-agent modeling[J]. Expert Systems with Applications, 2022, 187:115976. doi: 10.1016/j.eswa.2021.115976 URL
[13]	SCHUMANN B, FERRARO M, SURENDRA A, et al. Better design decisions through operational modeling during the early design phases[J]. Journal of Aerospace Information Systems, 2014, 11(4):195-210. doi: 10.2514/1.I010149 URL
[14]	ZHANG R W, SONG B F, PEI Y, et al. Improved method for subsystems performance trade-off in system-of-systems oriented design of UAV swarms[J]. Journal of Systems Engineering and Electronics, 2019, 30(4):720-737. doi: 10.21629/JSEE.2019.04.10
[15]	罗承昆, 陈云翔, 项华春, 等. 装备体系贡献率评估方法研究综述[J]. 系统工程与电子技术, 2019, 41(8):1789-1794. doi: 10.3969/j.issn.1001-506X.2019.08.16
	LUO C K, CHEN Y X, XIANG H C, et al. Review of the evaluation methods of equipment’s contribution rate to system-of-systems[J]. Systems Engineering and Electronics, 2019, 41(8):1789-1794. (in Chinese)
[16]	杨克巍, 杨志伟, 谭跃进, 等. 面向体系贡献率的装备体系评估方法研究综述[J]. 系统工程与电子技术, 2019, 41(2):311-321.
	YANG K W, YANG Z W, TAN Y J, et al. Review of the evaluation methods of equipment system of systems facing the contribution rate[J]. Systems Engineering and Electronics, 2019, 41(2):311-321. (in Chinese) doi: 10.3969/j.issn.1001-506X.2019.02.13
[17]	李际超, 杨克巍, 张小可, 等. 基于武器装备体系作战网络模型的装备贡献度评估[J]. 复杂系统与复杂性科学, 2016, 13(3):1-7.
	LI J C, YANG K W, ZHANG X K, et al. Equipment contribution degree evaluation method based on combat network of weapon system-of-systems[J]. Complex Systems and Complexity Science, 2016, 13(3):1-7. (in Chinese)
[18]	罗小明, 杨娟, 何榕. 基于任务-能力-结构-演化的武器装备体系贡献度评估与示例分析[J]. 装备学院学报, 2016, 27(3):7-13.
	LUO X M, YANG J, HE R. Research and demonstration on contribution evaluation of weapon equipment system based on task-capability-structare-evolution[J]. Journal of Equipment Academy, 2016, 27(3):7-13. (in Chinese)
[19]	许秉军, 李孟军, 李兴兵, 等. 装甲装备体系对抗仿真评估系统研究[C]// 中国自动化学会系统仿真专业委员会, 中国系统仿真学会仿真应用专业委员会 2007系统仿真技术及其应用学术会议论文集. 合肥: 中国科学技术大学出版社, 2007.
	XU B J, LI M J, LI X B, et al. Research on the armored equipment system-of-systems warfare simulation & effectiveness evaluation system[C]// Proceedings of the 2007 Academic Conference on System Simulation Technology and Its Applications. Hefei: University of Science and Technology of China, 2007. (in Chinese)
[20]	俞锦涛, 肖兵, 崔玉竹, 等. 基于时序网络仿真和贡献率的预警作战体系任务支持能力评估[J/OL]. 兵工学报:1-14[2023-09-15]. http://kns.cnki.net/kcms/detail/11.2176.tj.20230207.1410.004.html.
	YU J T, XIAO B, CUI Y Z, et al. Mission support capability assessment of early warning combat system-of-system based on temporal network simulation and contribution rate[J/OL]. Acta Armamentarii:1-14[2023-09-15]. http://kns.cnki.net/kcms/detail/11.2176.TJ.20221129.1639.002.html. (in Chinese)
[21]	李峻森, 方依宁, 张云安, 等. 面向任务的装备保障体系多Agent建模与评估方法[J]. 系统工程与电子技术, 2023, 45(1):279-290. doi: 10.12305/j.issn.1001-506X.2023.01.33
	LI J S, FANG Y N, ZHANG Y A, et al. Multi-agent modeling and evaluation method for mission-oriented equipment support SoS[J]. Systems Engineering and Electronics, 2023, 45(1):279-290. (in Chinese) doi: 10.12305/j.issn.1001-506X.2023.01.33
[22]	SHI L K, PEI Y, YUN Q J, et al. Agent-based effectiveness evaluation method and impact analysis of airborne laser weapon system in cooperation combat[J]. Chinese Journal of Aeronautics, 2023, 36(4):442-454.
[23]	YUN Q J, SONG B F, PEI Y. Modeling the impact of high energy laser weapon on the mission effectiveness of unmanned combat aerial vehicles[J]. IEEE Access, 2020, 8:32246-32257. doi: 10.1109/Access.6287639 URL
[24]	庞维建, 李辉, 黄谦, 等. 集群无人机要地攻防作战Multi-Agent建模仿真分析[J]. 信息工程大学学报, 2022, 23(5):617-625.
	PANG W J, LI H, HUANG Q, et al. Multi-agent based modeling and simulation of swarm UAV attack and defense operation for vital area[J]. Journal of Information Engineering University, 2022, 23(5):617-625. (in Chinese)
[25]	俞锦涛, 肖兵, 崔玉竹. 基于节点重要性和改进效能环的防空反导预警体系能力评估[J/OL]. 兵工学报:1-10[2023-09-15]. http://kns.cnki.net/kcms/detail/11.2176.TJ.20221129.1639.002.html.
	YU J T, XIAO B, CUI Y Z. Capability evaluation of air defense and anti-missile early warning system-of-system based on node importance and improved effectiveness loop[J/OL]. Acta Armamentarii:1-10[2023-09-15]. http://kns.cnki.net/kcms/detail/11.2176.TJ.20221129.1639.002.html. (in Chinese)
[26]	郭雷平, 段文博, 刘宇, 等. 基于OODA环的合成部队光电装备作战效能评估[J]. 兵工学报, 2022, 43(增刊1):177-182.
	GUO L P, DUAN W B, LIU Y, et al. Operational effectiveness evaluation of optoelectronic equipment for combined arms based on OODA loop[J]. Acta Armamentarii, 2022, 43(S1):177-182. (in Chinese) doi: 10.12382/bgxb.2022.A009
[27]	LI X, ZHAO X D, PU W. Knowledge-oriented modeling for influencing factors of battle damage in military industrial logistics:an integrated method[J]. Defense Technology, 2020, 16(3):571-587.
[28]	管清波, 于小红. 新型武器装备体系贡献度评估问题探析[J]. 装备学院学报, 2015, 26(3):1-5.
	GUAN Q B, YU X H. Research on evaluation of equipment’s contribution to system warfighting[J]. Journal of Equipment Academy, 2015, 26(3):1-5. (in Chinese)
[29]	王保华. 主动式激光制导导引头光学系统设计[D]. 长春: 中国科学院长春光学精密机械与物理研究所, 2012.
	WANG B H. Optical design and stray light analysis of active laser-guided seeker[D]. Changchun: Changchun Institute of Optics, Fine Mechanics and Physics, 2012. (in Chinese)
[30]	齐小刚, 李博, 范英盛, 等. 多约束下多无人机的任务规划研究综述[J]. 智能系统学报, 2020, 15(2):204-217.
	QI X G, LI B, FAN Y S, et al. A survey of mission planning on UAVs systems based on multiple constraints[J]. CAAI Transactions on Intelligent Systems, 2020, 15(2):204-217. (in Chinese)
[31]	鲁飞, 鲁照权, 牛晨, 等. 基于改进蚁群算法的三维路径规划研究[J]. 传感器与微系统, 2022, 41(1):45-49.
	LU F, LU Z Q, NIU C, et al. Research on 3D path planning based on improved ant colony algorithm[J]. Transducer and Microsystem Technologies, 2022, 41(1):45-49. (in Chinese)
[32]	于飞, 马慧, 陈斐楠, 等. 三维海底栅格地形在潜器路径规划中的应用[J]. 计算机工程与应用, 2016, 52(5):241-245.
	YU F, MA H, CHEN F N, et al. Application of 3D grid seabed terrain in submersible path planning[J]. Computer Engineering and Applications, 2016, 52(5):241-245. (in Chinese)