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UAV cooperative air combat maneuver decision based on multi-agent reinforcement learning

Journal of Systems Engineering and Electronics 2021年第6期32卷 1421-1438页

作者： ZHANG Jiandong YANG Qiming SHI Guoqing LU Yi WU Yong School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710072China Shenyang aircraft Design Institute Shenyang 110035China

In order to improve the autonomous ability of unmanned aerial vehicles(UAV)to implement air combat mission,many artificial intelligence-based autonomous air combat maneuver decision-making studies have been carried out,but these studies are often aimed at individual decision-making in 1 v1 scenarios which rarely happen in actual air *** on the research of the 1 v1 autonomous air combat maneuver decision,this paper builds a multi-UAV cooperative air combat maneuver decision model based on multi-agent reinforcement ***,a bidirectional recurrent neural network(BRNN)is used to achieve communication between UAV individuals,and the multi-UAV cooperative air combat maneuver decision model under the actor-critic architecture is ***,through combining with target allocation and air combat situation assessment,the tactical goal of the formation is merged with the reinforcement learning goal of every UAV,and a cooperative tactical maneuver policy is *** simulation results prove that the multi-UAV cooperative air combat maneuver decision model established in this paper can obtain the cooperative maneuver policy through reinforcement learning,the cooperative maneuver policy can guide UAVs to obtain the overall situational advantage and defeat the opponents under tactical cooperation.

关键词： decision-making air combat maneuver cooperative air combat reinforcement learning recurrent neural network

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Task assignment under constraint of timing sequential for cooperative air combat

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Journal of Systems Engineering and Electronics 2016年第4期27卷 836-844页

作者： Chengwei Ruan Zhongliang Zhou Hongqiang Liu Haiyan Yang Aeronautics and Astronautics Engineering College Air Force Engineering UniversityXi'an710038China College of Instrument Science and Technology Tsinghua UniversityBeijing100084China

According to the previous achievement, the task assignment under the constraint of timing continuity for a cooperative air combat is studied. An extensive task assignment scenario with the background of the cooperative air combat is proposed. The utility and time of executing a task as well as the continuous combat ability are defined. The concept of the matching method of weapon and target is modified based on the analysis of the air combat scenario. The constraint framework is also redefined according to a new objective function. The constraints of timing and continuity are formulated with a new method, at the same time, the task assignment and integer programming models of the cooperative combat are established. Finally, the assignment problem is solved using the integrated linear programming software and the simulation shows that it is feasible to apply this modified model in the cooperative air combat for tasks cooperation and it is also efficient to optimize the resource assignment.

关键词： cooperative air combat task assignment timing constraint task utility integer programming

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Autonomous maneuver strategy of swarm air combat based on DDPG

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Autonomous Intelligent Systems 2021年第1期1卷 232-243页

作者： Luhe Wang Jinwen Hu Zhao Xu Chunhui Zhao School of Automation Northwestern Polytechnical UniversityXi’an 710129China School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710129China

Unmanned aerial vehicles(UAVs)have been found significantly important in the air combats,where intelligent and swarms of UAVs will be able to tackle with the tasks of high complexity and *** key to empower the UAVs with such capability is the autonomous maneuver decision *** this paper,an autonomous maneuver strategy of UAV swarms in beyond visual range air combat based on reinforcement learning is ***,based on the process of air combat and the constraints of the swarm,the motion model of UAV and the multi-to-one air combat model are ***,a two-stage maneuver strategy based on air combat principles is designed which include inter-vehicle collaboration and target-vehicle ***,a swarm air combat algorithm based on deep deterministic policy gradient strategy(DDPG)is proposed for online strategy ***,the effectiveness of the proposed algorithm is validated by multi-scene *** results show that the algorithm is suitable for UAV swarms of different scales.

关键词： Deep reinforcement learning cooperative air combat Swarm Maneuver strategy

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cooperative Threat Assessment of Multi-aircrafts Based on Synthetic Fuzzy Cognitive Map

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Journal of Shanghai Jiaotong university(Science) 2012年第2期17卷 228-232页

作者：陈军俞冠华高晓光 School of Electronics and Information Northwest Polytechnical University Department of Automation Shanghai Jiaotong University

Threat assessment is one of the most important parts of the tactical decisions,and it has a very important influence on task *** application of fuzzy cognitive map(FCM) for target threat assessment in the air combat is *** the fact that the aircrafts participated in the cooperation may not have the same threat assessment mechanism,two different FCM models are *** the method of combination,the model of cooperative threat assessment in air combat of multi-aircrafts is *** results show preliminarily that the method is reasonable and *** FCM for threat assessment is feasible.

关键词： threat assessment synthetic fuzzy cognitive map(FCM) multi-aircrafts cooperative air combat

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