基于混合自适应遗传算法的相控阵雷达任务调度

doi:10.3969/j.issn.1000-1093.2017.09.013

摘要/Abstract

摘要： 针对相控阵雷达任务调度NP难题，提出一种混合自适应遗传算法进行求解。在构建相控阵雷达任务调度优化模型的基础上，通过混沌理论优化初始种群，采取精英保留和混合排名的选择策略以及设计自适应的交叉、变异算子来提升算法的搜索性能；在自适应遗传算法的框架下，提出启发式脉冲交错算法，以利用雷达任务中的等待期来交错执行其他任务的发射期或接收期。仿真结果表明：相比于基于遗传算法的调度方法，改进算法的搜索效率更高、结果更优；相比于传统启发式算法，改进算法的调度成功率、时间利用率和实现价值率均得到了提升，并有效降低了时间偏移率。

关键词: 兵器科学与技术, 相控阵雷达, 调度, 自适应遗传算法, 混沌理论, 脉冲交错

Abstract: A hybrid adaptive genetic algorithm is proposed for the task scheduling of phased array radar. An optimal scheduling model for phased array radar is established. The performance and efficiency of the algorithm are improved by optimizing the initial population by the chaos theory, adopting the selection strategy of elite reservation and mixed ranking, and designing the adaptive crossover and mutation operators. A heuristic pulse interleaving algorithm is presented based on the adaptive genetic algorithm. It could utilize the waiting period in a task to execute the transmitting period or receiving period of other task. The simulated results demonstrate that the proposed algorithm provides better results and search solutions more quickly than the genetic algorithm. Moreover, compared with the heuristic scheduling algorithm, the proposed algorithm improves the scheduling success ratio, time utilization ratio and high value ratio, and decreases the average time shift ratio efficiently. Key

Key words: ordnancescienceandtechnology, phasedarrayradar, scheduling, adaptivegeneticalgorithm, chaostheory, pulseinterleaving

中图分类号:

TN954⁺.2

张浩为，谢军伟，张昭建，宗彬锋，陈唐军. 基于混合自适应遗传算法的相控阵雷达任务调度[J]. 兵工学报, 2017, 38(9): 1761-1770.

ZHANG Hao-wei, XIE Jun-wei, ZHANG Zhao-jian, ZONG Bin-feng, CHEN Tang-jun. Task Scheduling of Phased Array Radar Based on Hybrid Adaptive Genetic Algorithm[J]. Acta Armamentarii, 2017, 38(9): 1761-1770.

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