一种智能距离门拉断(RGPO)干扰方法

Ruitao Jia, Tianxian Zhang, Yuanhang Wang, Yanhong Deng, L. Kong
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引用次数: 3

摘要

针对自防御干扰中的距离门拉断(RGPO)干扰,在未知环境模型下研究了一种最优多帧RGPO干扰策略。提出了一种基于黑盒优化技术的多帧RGPO干扰策略优化方法,解决了RGPO干扰策略优化问题。首先,以拉离成功率为目标函数,构建了RGPO干扰策略的多帧优化模型;然后,为了改善干扰性能,提出了一种基于蒙特卡罗预测适应度函数的粒子群优化算法(MC-PSO)。最后给出了数值仿真结果,验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Intelligent Range Gate Pull-off (RGPO) Jamming Method
In this paper, considering a range gate pull-off (RGPO) jamming for self-defense jamming, an optimal multiframe RGPO jamming strategy is investigated with unknown environment model. The optimal RGPO jamming strategy problem is solved by proposing a multi-frame RGPO jamming strategy optimization method based on black-box optimization technique. Firstly, we construct a multi-frame optimization model of RGPO jamming strategy by choosing the success rate of pull-off as the objective function. Then, to improve the jamming performance, a particle swarm optimization(PSO) algorithm based on Monte Carlo prediction fitness function(MC-PSO) is proposed. Finally, numerical simulation results are provided to verify the validity of the proposed method.
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