Optimization of UAV Smoke Screen Cooperative Masking Using Improved PSO
DOI:
https://doi.org/10.54097/pgq23f42Keywords:
Smoke screen jamming, Particle swarm optimization, Geometric occlusion model, Cooperative defenseAbstract
Aiming at the scheduling problem of UAV smoke screen cooperative masking of incoming missiles, this paper proposes a hierarchical solution framework that combines geometric analysis and intelligent optimization. Firstly, based on kinematics and line of sight occlusion geometric analysis, the three-dimensional occlusion judgment is simplified to discrete point judgment, and the effective occlusion time of the benchmark strategy is calculated to be 1.3920 seconds. Then, an optimization model with the maximum occlusion time is established, and the particle swarm algorithm with dynamically adjusted inertial weight is used to solve the problem, and the optimal occlusion duration of 4.5900 seconds and the corresponding strategy are obtained. It is further extended to the scene of three smoke bombs being dropped consecutively on a single machine, and the effective occlusion time is increased to 6.4000 seconds by integrating Latin hypercube initialization, dynamic adjustment of learning factors and chaos perturbation strategies. The results show that the proposed improved particle swarm algorithm can effectively solve such high-dimensional nonlinear constraint optimization problems, and provide a theoretical basis and feasible scheme for the real-time planning of UAV active defense.
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