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 

机构地区：[1]School of Automation,Northwestern Polytechnical University,Xi'an,710129,China [2]Shaanxi Province Key Laboratory of Flight Control and Simulation Technology,Xi'an,710129,China [3]Science and Technology on Aircraft Control Laboratory,FACRI,Xi'an,710065,China

出　　处：《Defence Technology（防务技术）》2022年第6期1006-1022,共17页Defence Technology

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。

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 combat.However,prior research on occupational decision-making in BVR air combat has mostly been limited to one-on-one scenarios.As such,this study presents a practical cooperative occupation decision-making methodology for use with multiple UCAVs.The weapon engagement zone(WEZ)and combat geometry were first used to develop an advantage function for situational assessment of one-on-one engagement.An encircling advantage function was then designed to represent the cooperation of UCAVs,thereby establishing a cooperative occupation model.The corresponding objective function was derived from the one-on-one engagement advantage function and the encircling advantage function.The resulting model exhibited similarities to a mixed-integer nonlinear programming(MINLP)problem.As such,an improved discrete particle swarm optimization(DPSO)algorithm was used to identify a solution.The 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 engagement.Simulated results showed these solutions varied with initial conditions and weighting coefficients.This occupation process,based on formation switching,effectively demonstrates the viability of the proposed technique.These cooperative occupation results could provide a theoretical framework for subsequent research in cooperative BVR air combat.

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

分 类 号：E926.3[军事—军事装备学]