Cooperative Guidance Scheme for Flight of Multiple Combat UA Vs against a Non-Accelerating Moving Target

Malik, Zishan Ahmed; Haydar, Muhammad Farooq; Riaz, Jamshed

doi:10.1109/ibcast51254.2021.9393309

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…where is the proportional constant; is the angle between the missile velocity vector and reference line; is the angle between the sight line and reference line [40], [41].…”

Section: End Criteriamentioning

confidence: 99%

High-Fidelity Decision-Making and Simulation for Cooperative Autonomous Air Combat Considering the Effect of Flight Controller

Wang

Wang²,

et al. 2022

IEEE Access

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In the past decade, how improving the fidelity of maneuver gaming and the synergy of target allocation has become key issues in cooperative autonomous air combat researches. To address these two problems, this study proposes a maneuver decision-making algorithm based on an optimized dynamic Bayesian network and a target allocation decision-making algorithm based on an optimized hybrid particle swarm optimization. In maneuvering decision-making, the state transition's reliability and the air combat's autonomy are enhanced through considering the effect of sliding mode control. The Bayesian network is improved through introducing a strategy for dynamic prior probability updating. The computation is reduced and the efficiency is increased through pruning the minimax search tree according to visual prediction. In target allocation decision-making, the algorithm's convergence speed is greatly accelerated and the solution's global optimality is improved through introducing immigrant particles. The algorithm's application scope is expanded through proposing a solution principle about unequal quantity combat situations. Furthermore, the end criterion is specially designed to fit real-world combats through introducing a fire control. The simulation results show that the designed decision-making algorithms are more effective in solving the problem of cooperative autonomous air combat, which shows that the various improvements introduced in this study are reasonable and effective.INDEX TERMS Cooperative autonomous air combat, maneuver decision-making, target allocation decision-making, sliding mode controller, dynamic Bayesian network, hybrid particle swarm optimization.

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“…where is the proportional constant; is the angle between the missile velocity vector and reference line; is the angle between the sight line and reference line [40], [41].…”

Section: End Criteriamentioning

confidence: 99%

High-Fidelity Decision-Making and Simulation for Cooperative Autonomous Air Combat Considering the Effect of Flight Controller

Wang

Wang²,

et al. 2022

IEEE Access

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“…High-speed unmanned aerial vehicle (UAV) is a general term for a class of aircraft used as precision-guided weapons to attack enemy targets, such as the suicide UAV, missile, and so on [ 1 , 2 ]. Compared with the manned fighter, UAV has the advantages of fast dispatch speed, strong mobility, zero casualties, and convenient multi aircraft cooperative operation [ 3 – 5 ].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Guidance and Control Methods for Missile Swarm

Huang

Zhao

Zhang

2022

Computational Intelligence and Neuroscience

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High-speed unmanned aerial vehicles (UAVs) are more and more widely used in both military and civil fields at present, especially the missile swarm attack, and will play an irreplaceable key role in the future war as a special combat mode. This study summarizes the guidance and control methods of missile swarm attack operation. First, the traditional design ideas of the guidance and control system are introduced; then, the typical swarm attack guidance and control methods are analyzed by taking their respective characteristics into considering, and the limitations of the traditional design methods are given. On this basis, the study focuses on the advantages of intelligent integrated guidance and control design over traditional design ideas, summarizes the commonly used integrated guidance and control design methods and their applications, and explores the cooperative attack strategy of missile swarm suitable for the integrated guidance and control system. Finally, the challenges of missile swarm guidance and control are described, and the problems worthy of further research in the future are prospected. Summarizing the guidance and control methods of missile will contribute to the innovative research in this field, so as to promote the rapid development of unmanned swarm attack technology.

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