A Multi-UCAV cooperative occupation method based on weapon engagement zones for beyond-visual-range air combat

作     者：Wei-hua Li Jing-ping Shi Yun-yan Wu Yue-ping Wang Yong-xi Lyu Wei-hua Li;Jing-ping Shi;Yun-yan Wu;Yue-ping Wang;Yong-xi Lyu

作者机构：School of AutomationNorthwestern Polytechnical UniversityXi'an710129China Shaanxi Province Key Laboratory of Flight Control and Simulation TechnologyXi'an710129China Science and Technology on Aircraft Control LaboratoryFACRIXi'an710065China 

出 版 物：《Defence Technology（防务技术）》 (Defence Technology)

年 卷 期：2022年第18卷第6期

页      面：1006-1022页

核心收录：

学科分类：082601[工学-武器系统与运用工程] 08[工学] 0826[工学-兵器科学与技术] 

基　　金：supported by the National Natural Science Foundation of China(No.61573286) the Aeronautical Science Foundation of China(No.20180753006) the Fundamental Research Funds for the Central Universities(3102019ZDHKY07) the Natural Science Foundation of Shaanxi Province(2020JQ-218) the Shaanxi Province Key Laboratory of Flight Control and Simulation Technology 

主　　题：Unmanned combat aerial vehicle Cooperative occupation Beyond-visual-range air combat Weapon engagement zone Discrete particle swarm optimization Formation switching 

摘      要：Recent advances in on-board radar and missile capabilities,combined with individual payload limitations,have led to increased interest in the use of unmanned combat aerial vehicles(UCAVs)for cooperative occupation during beyond-visual-range(BVR)air ***,prior research on occupational decision-making in BVR air combat has mostly been limited to one-on-one *** such,this study presents a practical cooperative occupation decision-making methodology for use with multiple *** weapon engagement zone(WEZ)and combat geometry were first used to develop an advantage function for situational assessment of one-on-one *** encircling advantage function was then designed to represent the cooperation of UCAVs,thereby establishing a cooperative occupation *** corresponding objective function was derived from the one-on-one engagement advantage function and the encircling advantage *** resulting model exhibited similarities to a mixed-integer nonlinear programming(MINLP)*** such,an improved discrete particle swarm optimization(DPSO)algorithm was used to identify a *** occupation process was then converted into a formation switching task as part of the cooperative occupation model.A series of simulations were conducted to verify occupational solutions in varying situations,including two-on-two *** results showed these solutions varied with initial conditions and weighting *** occupation process,based on formation switching,effectively demonstrates the viability of the proposed *** cooperative occupation results could provide a theoretical framework for subsequent research in cooperative BVR air combat.