基于灰狼算法的抗干扰跳频序列设计
Design of anti-jamming frequency-hopping sequence based on grey wolf algorithm
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摘要: 为了提高跳频通信系统的抗干扰能力,本文提出一种结合干扰信息综合考虑跳频序列的汉明相关性、均匀性、被干扰概率和跳频增益的抗干扰跳频序列优化设计方法。使用改进灰狼算法求解优化问题,提出新型反向学习策略和使用莱维飞行的个体信息交流机制,提升灰狼算法性能。通过基本测试函数的仿真实验表明本文的改进灰狼算法比其他灰狼算法有更好的收敛速度和求解精度。本文的抗干扰跳频序列优化设计结果表明,在多种干扰情况下,本文方法设计的跳频序列相比于传统跳频序列和宽间隔跳频序列具有更强的抗干扰能力。
Abstract: In order to improve the anti-jamming ability of the frequency-hopping communication system, an optimized design method of anti-jamming frequency-hopping sequence is proposed. This method combines the jamming information to comprehensively consider the Hamming-correlation properties, uniformity, interference probability and frequency-hopping gain of the frequency-hopping sequence. The improved grey wolf algorithm is used to solve the above optimization problem. A new opposition-based learning strategy and individual information exchange mechanism using Levy flight are proposed to improve the performance of the grey wolf algorithm. The experimental results about basic test functions show that the improved grey wolf algorithm is superior to other grey wolf algorithms in convergence speed and solution accuracy. And the optimized design results of anti-jamming frequency-hopping sequence show that it’s anti-jamming ability is stronger than the traditional frequency-hopping sequence and the wide-gap frequency-hopping sequence under various jamming background.