摘要
为了解决分布式通信干扰场景下面临的资源分配效率低、干扰效益无保障等问题,结合通信干扰资源分配数学模型,设计了一种改进的粒子群算法。首先设计了分布式通信干扰场景并构建了通信干扰资源分配模型,以最大化干扰效益作为目标函数;其次采用自适应惯性因子和学习因子,并引入遗传变异策略和精英保留策略,提出一种改进的粒子群算法,最后对不同场景规模的通信干扰资源分配进行仿真实验。结果表明,相比小生境遗传算法、粒子群算法、遗传算法,改进的粒子群算法在不同场景规模下,均能获得更优的干扰效益,性能方面具备整体干扰效益更高、算法收敛速度更快、算法收敛误差更小等优势。所设计的改进粒子群算法可应用在分布式通信干扰场景中,为指挥决策提供参考。
In order to solve the problems of low resource allocation efficiency and insecure jamming benefit in distributed communication jamming scenarios,an improved particle swarm optimization algorithm was designed based on the mathematical model of communication jamming resource allocation.First,a distributed communication jamming scenario was designed and a communication jamming resource allocation model was constructed,with the maximum jamming benefit as the objective function;Secondly,an improved particle swarm optimization algorithm was proposed by using adaptive inertia factor and learning factor,and introducing genetic mutation strategy and elite retention strategy.The results show that,compared with niche genetic algorithm,particle swarm optimization algorithm and genetic algorithm,the improved particle swarm optimization algorithm can obtain better jamming benefit in different scene scales,and has the advantages of higher overall jamming benefit,faster algorithm convergence speed and smaller algorithm convergence error in terms of performance.The improved particle swarm optimization algorithm can be applied to the distributed communication jamming scene to provide reference for command decision-making.
作者
赵经纬
张君毅
李佳
ZHAO Jingwei;ZHANG Junyi;LI Jia(The 54th Research Institution of China Electronics Technology Group Corporation,Shijiazhuang,Hebei 050081,China;Hebei Province Key Laboratory of Electromagnetic Spectrum Cognition and Control,Shijiazhuang,Hebei 050081,China)
出处
《河北工业科技》
CAS
2023年第1期52-58,共7页
Hebei Journal of Industrial Science and Technology
基金
国家自然科学基金(U19B2028)。
关键词
人工智能技术
粒子群算法
改进粒子群算法
分布式通信干扰
资源分配
artificial intelligence technology
particle swarm optimization
improved particle swarm optimization
distributed communication jamming
resource allocation
