摘要
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.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Key words
multi-unmanned aerial vehicle(multi-UAV)cooperation/track deception jamming/netted radar/improved whale optimization algorithm分类
信息技术与安全科学
