| 摘要: |
| 多机协同对组网雷达系统进行航迹欺骗干扰属于大规模优化问题，往往需要利用群体智能算法优化无人机的飞行任务，然而采用传统群体智能算法优化时往往会出现收敛速度慢、求解精度低等问题。针对这一问题，对标准鲸鱼优化算法进行了改进，提出了一种基于改进鲸鱼优化算法的多无人机协同欺骗干扰技术。首先建立了多无人机协同欺骗干扰组网雷达的数学模型以及对应的优化函数，然后在标准鲸鱼优化算法的基础上引入了自适应惯性权值，提高了算法的全局搜索能力和收敛速度。仿真实验表明，固定无人机数量为9架时，利用改进鲸鱼、标准鲸鱼、粒子群、蚁群4种算法分别优化多机协同欺骗干扰模型，得出改进鲸鱼优化算法平均运行时间最短，迭代次数最少，同时优化产生的实际航迹与理论值误差最小；逐步增加无人机数量至20架，利用上述四种算法进行模型求解时得出改进鲸鱼优化算法在不同无人机架数的条件下产生的假目标航迹条数均优于其他3种算法。 |
| 关键词: 多无人机（multi-UAV）协同 航迹欺骗干扰 组网雷达 改进鲸鱼优化算法 |
| DOI：10.20079/j.issn.1001-893x.230213002 |
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| 基金项目: |
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| Multi-UAV Cooperative Deception Jamming Technology Based on Improved Whale Optimization Algorithm |
| DING Chencong,YE Ziqing |
| (Unit 92728 of PLA,Shanghai 200442,China) |
| Abstract: |
| Multi-unmanned aerial vehicle(multi-UAV) cooperative track deception jamming against netted radar system is a large-scale optimization problem.It is often necessary to use swarm intelligence algorithms to optimize the flight missions of UAVs.However,when traditional swarm intelligence algorithms are used for optimization,problems such as slow convergence speed and low solution accuracy often occur.For above problems,the whale optimization algorithm is improved and a multi-UAV cooperative deception jamming technology based on improved whale optimization algorithm is proposed.Firstly,the mathematical model of multi-UAV cooperative deception jamming to netted radar is constructed and the corresponding optimization function is established.Secondly,the adaptive inertia weight is introduced on the basis of the whale optimization algorithm,which improves the global search ability and convergence speed of the algorithm.The four algorithms including improved whale,whale,particle swarm and ant colony are used to optimize the multi-UAV cooperative deception jamming model respectively.It is concluded that the improved whale optimization algorithm has the shortest average running time,the least number of iterations,and the minimum error between the actual track and the theoretical value.When the number of UAVs is gradually increased to 20,the above four algorithms are used to solve the same model,it is concluded that the improved whale optimization algorithm is superior to other three algorithms in the number of deception tracks generated under the condition of different number of UAVs. |
| Key words: multi-unmanned aerial vehicle(multi-UAV) cooperation track deception jamming netted radar improved whale optimization algorithm |
