基于混合自适应遗传算法的相控阵雷达任务调度

发布时间：2018-03-10 08:40

本文选题：兵器科学与技术　切入点：相控阵雷达　出处：《兵工学报》2017年09期 　论文类型：期刊论文

【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。
[Abstract]:Aiming at the NP problem of phased array radar task scheduling, a hybrid adaptive genetic algorithm is proposed to solve the problem. On the basis of constructing the optimization model of phased array radar task scheduling, the initial population is optimized by chaos theory. In order to improve the search performance of the algorithm, the selection strategy of elite reservation and hybrid ranking and the design of adaptive crossover and mutation operators are adopted to improve the search performance of the algorithm. In the framework of adaptive genetic algorithm, a heuristic pulse interleaving algorithm is proposed. In this paper, the waiting period of radar task is used to interleave the transmitting or receiving periods of other tasks. The simulation results show that compared with the genetic algorithm, the improved algorithm is more efficient and the result is better than that of the genetic algorithm. Compared with the traditional heuristic algorithm, the scheduling success rate, time utilization rate and realization value rate of the improved algorithm are improved, and the time offset rate is reduced effectively.
【作者单位】：空军工程大学防空反导学院;94710部队;94921部队;
【基金】：国家自然科学基金青年科学基金项目(61503408)
【分类号】：TN958.92;TP18

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