高速目标分阶段博弈拦截制导策略

doi:10.7527/S1000-6893.2021.25598

电子电气工程与控制

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高速目标分阶段博弈拦截制导策略

王鑫¹, 闫杰², 孟廷伟¹

1. 西北工业大学航天学院, 西安 710072;
2. 西北工业大学无人系统技术研究院, 西安 710072

收稿日期:2021-03-30 修回日期:2021-05-05 出版日期:2022-09-15 发布日期:2021-08-25
通讯作者: 孟廷伟,E-mail:mtw18234154928@163.com E-mail:mtw18234154928@163.com
基金资助:
国家自然科学基金(61873210, 61871302)

High-speed target multi-stage interception scheme based on game theory

WANG Xin¹, YAN Jie², MENG Tingwei¹

1. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China

Received:2021-03-30 Revised:2021-05-05 Online:2022-09-15 Published:2021-08-25
Supported by:
National Natural Science Foundation of China (61873210, 61871302)

摘要/Abstract

摘要： 基于分阶段博弈模型对吸气式高超声速飞行器的拦截问题进行了研究, 提出了由两枚拦截弹组成的拦截系统的分阶段拦截方案。依据高超声速目标的机动特征将拦截过程分为两个阶段。在第1个阶段, 拦截系统依据目标运动特征及约束条件计算得到目标在预测交汇平面的可达范围和虚拟拦截点。拦截弹Ⅰ执行基于虚拟交班点的中制导以及基于广义末制导律的末制导过程。由于目标运动状态受到约束条件的限制, 使得目标在突防过程中可行范围和机动能力大幅减弱。在第2个阶段, 基于博弈理论和直觉模糊理论建立拦截弹Ⅱ-目标直觉模糊博弈模型。通过设计拦截弹-目标策略集以及多属性评估模型获得满足要求的均衡策略模型, 通过求解非线性规划问题最终使得我方拦截最终博弈获胜。通过拦截弹动态策略和固定策略的仿真对比说明所提博弈制导策略的有效性。

关键词: 分阶段拦截, 目标可行域, 直觉模糊博弈, 决策评估, 纳什均衡

Abstract: Interception of the air-breathing hypersonic vehicle is studied based on the staged game model in this paper. The solution based on the interception system made of two interceptors are proposed. According to the maneuvering characteristics of the hypersonic target, the process of interception is divided into two stages. In the first stage, the interception system calculates the target's reachable range and virtual interception point in the predicted intersection plane according to the target's motion characteristics and constraint conditions. Interceptor Ⅰ executes mid-guidance based on the virtual handover point, and terminal guidance based on the generalized terminal guidance law. Because the movement of the target is restricted by the constraints, the feasible range and maneuvering ability of the target are greatly weakened in the penetration process. In the second stage of the interception process, the Interceptor Ⅱ-target intuitionistic fuzzy game model is established based on the game theory and the intuitionistic fuzzy theory. The equilibrium strategy model is obtained through interceptor-target strategy sets and the multi-attribute evaluation model. Our side wins the game by solving the nonlinear programming problem. Finally, the numerical results of the dynamic strategy and the fixed strategy are compared to show the effectiveness of the proposed guidance strategy.

Key words: interception in stages, target feasible region, intuitionistic fuzzy game, decision evaluation, Nash equilibrium

中图分类号:

V448.23

王鑫, 闫杰, 孟廷伟. 高速目标分阶段博弈拦截制导策略[J]. 航空学报, 2022, 43(9): 325598.

WANG Xin, YAN Jie, MENG Tingwei. High-speed target multi-stage interception scheme based on game theory[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 325598.

参考文献

[1] ZHANG D Y, LEI H M, SHAO L, et al. Interceptor trajectory programming for near space hypersonic target[J]. Journal of National University of Defense Technology, 2015, 37(3): 91-96 (in Chinese). 张大元, 雷虎民, 邵雷, 等. 临近空间高超声速目标拦截弹弹道规划[J]. 国防科技大学学报, 2015, 37(3): 91-96.
[2] SHAFERMAN V, SHIMA T. Cooperative optimal guidance laws for imposing a relative intercept angle[J]. Journal of Guidance, Control, and Dynamics, 2015, 38(8): 1395-1408.
[3] BALHANCE N, WEISS M, SHIMA T. Cooperative guidance law for intrasalvo tracking[J]. Journal of Guidan-ce, Control, and Dynamics, 2017, 40(6): 1441-1456.
[4] NOBAHARI H, NASROLLAHI S. A nonlinear robust model predictive differential game guidance algorithm based on the particle swarm optimization[J]. Journal of the Franklin Institute, 2020, 357(15): 11042-11071.
[5] SHAFERMAN V, SHIMA T. Cooperative differential games guidance laws for imposing a relative intercept angle[J]. Journal of Guidance, Control, and Dynamics, 2017, 40(10): 2465-2480.
[6] GUO Z Y, WANG C L, QIAN H, et al. Cooperative intercepting guidance law for large maneuvering target with impact angle constraint[J]. Journal of Northwestern Polytechnical University, 2020, 38(6): 1257-1265 (in Chinese). 郭正玉, 王超磊, 钱航, 等. 带有攻击角约束的大机动目标协同攻击制导律[J]. 西北工业大学学报, 2020, 38(6): 1257-1265.
[7] YUKSEK B, URE N K, INALHAN G. Cooperative interception of a highly manoeuvrable aerial target[C]//2018 AIAA Guidance, Navigation, and Control Conference. Reston: AIAA, 2018: 1581.
[8] CHEN Z Y, YU J L, DONG X W, et al. Three-dimensional cooperative guidance strategy and guidance law for intercepting highly maneuvering target[J]. Chinese Journal of Aeronautics, 2021, 34(5): 485-495.
[9] GAUDET B, FURFARO R, LINARES R. Reinforcement learning for angle-only intercept guidance of maneuvering targets[J]. Aerospace Science and Technology, 2020, 99: 105746.
[10] WEI M Y, CUI Z D, LI Y Q. Review and future development of multi-missile coordinated interception[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(S1): 723804 (in Chinese). 魏明英, 崔正达, 李运迁. 多弹协同拦截综述与展望[J]. 航空学报, 2020, 41(S1): 723804.
[11] LI H N, LEI H M, ZHAI D L, et al. Tracking oriented dynamics modeling of airbreathing hypersonic vehicles[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(6): 1651-1664 (in Chinese). 李海宁, 雷虎民, 翟岱亮, 等. 面向跟踪的吸气式高超声速飞行器动力学建模[J]. 航空学报, 2014, 35(6): 1651-1664.
[12] LI H F. Giuidance and control technology of hypersonic vehicle[M]. Beijing: China Astronautic Publishing House, 2012: 188-189 (in Chinese). 李惠峰. 高超声速飞行器制导与控制技术[M]. 北京: 中国宇航出版社, 2012: 188-189.
[13] LIU X. Research on trajectory optimization and guidance for hypersonic cruise vehicles[D]. Wuhan: Huazhong University of Science and Technology, 2017: 76-78 (in Chinese). 刘星. 高超声速巡航飞行器轨迹优化与制导方法研究[D]. 武汉: 华中科技大学, 2017: 76-78.
[14] CHEN J M, ZHANG D M, LIU D, et al. A network selection algorithm based on improved genetic algorithm[C]//2018 IEEE 18th International Conference on Communication Technology. Piscataway: IEEE Press, 2018: 209-214.
[15] SUN S, ZHOU D, ZHOU J Y, et al. A generalized design method for three-dimensional guidance laws[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2017, 231(1): 47-60.
[16] LI S H, DING Y, GAO Z L. UAV air combat maneuvering decision based on intuitionistic fuzzy game theory[J]. Systems Engineering and Electronics, 2019, 41(5): 1063-1070 (in Chinese). 李世豪, 丁勇, 高振龙. 基于直觉模糊博弈的无人机空战机动决策[J]. 系统工程与电子技术, 2019, 41(5): 1063-1070.
[17] CHEN X, LIU M, HU Y X. Study on UAV offensive/defensive game strategy based on uncertain information[J]. Acta Armamentarii, 2012, 33(12): 1510-1515 (in Chinese). 陈侠, 刘敏, 胡永新. 基于不确定信息的无人机攻防博弈策略研究[J]. 兵工学报, 2012, 33(12): 1510-1515.
[18] BRIKAA M G, ZHENG Z S, AMMAR E S. Resolving indeterminacy approach to solve multi-criteria zero-sum matrix games with intuitionistic fuzzy goals[J]. Mathematics, 2020, 8(3): 305.
[19] LLAMAZARES B. Using interval weights in MADM problems[J]. Computers & Industrial Engineering, 2019, 136: 345-354.
[20] ASSAUL V N, LASHCHENOV V K. Mixing strategies in the matrix game[J]. Journal of Physics: Conference Series, 2020, 1515(3): 032011.
[21] XU Z S, YAGER R R. Some geometric aggregation operators based on intuitionistic fuzzy sets[J]. International Journal of General Systems, 2006, 35(4): 417-433.
[22] LI Z Y, HUANG T, CHEN S M, et al. Overview of constrained optimization evolutionary algorithms[J]. Journal of Software, 2017, 28(6): 1529-1546 (in Chinese). 李智勇, 黄滔, 陈少淼, 等. 约束优化进化算法综述[J]. 软件学报, 2017, 28(6): 1529-1546.
[23] LIANG Y Q, HAN C Z, SUN Y J, et al. Modeling and multiple-model estimation of invariable-structure semi-ballistic reentry vehicle[J]. Acta Automatica Sinica, 2011, 37(6): 700-712 (in Chinese). 梁勇奇, 韩崇昭, 孙耀杰, 等. 不变结构半弹道式再入飞行器的建模与多模型方法估计[J]. 自动化学报, 2011, 37(6): 700-712.
[24] PATTERSON M A, RAO A V. Gpops-ii[J]. ACM Transactions on Mathematical Software, 2014, 41(1): 1-37.

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

高速目标分阶段博弈拦截制导策略

High-speed target multi-stage interception scheme based on game theory

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