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基于增强型龙格库塔优化算法的跳频序列设计

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跳频技术具有优秀的抗干扰性能和多址组网性能,跳频序列(FHS)作为其关键,在设计时面临性能指标差、难以兼顾多指标的问题。提出一种基于增强型龙格库塔优化算法(ERUN)的跳频序列设计方法。利用跳频序列的汉明相关性、复杂度、均匀性和平均跳频间隔构建目标函数,建立适用于启发式优化算法的跳频序列设计模型。针对龙格库塔优化算法(RUN)在复杂优化问题上收敛速度慢、寻优精度差的问题,提出增强型龙格库塔优化算法。利用混沌反向学习机制提高初始种群质量,基于二次插值法得到更好的个体更新方向,并根据自适应t分布扰动帮助种群跳出局部最优。在6个基准测试函数和目标函数上的测试结果表明,与RUN的3个最新变体相比,ERUN具有更快的收敛速度和更高的解精度。将得到的跳频序列应用于跳频系统中,实验结果表明,该方法在固定干扰环境下误码率为4%左右,在变化干扰环境下误码率没有明显上升,展现出了较强的抗干扰能力和复杂环境适应能力。
Design of Frequency-Hopping Sequence Based on Enhanced Runge Kutta Optimizer
Frequency-hopping technology has excellent anti-jamming and multiple access networks.Frequency-Hopping Sequence(FHS)is faced with the problems of poor performance index and difficulty in considering multiple indexes in design.Therefore,a design method of FHS based on an Enhanced Runge-Kutta optimizer(ERUN)is proposed.First,an objective function is constructed based on the Hamming correlation,complexity,uniformity,and average frequency-hopping interval of the FHS,and a design model of the FHS suitable for a heuristic optimization algorithm is established.Thereafter,aiming at the slow convergence speed and poor optimization accuracy of the Runge-Kutta optimizer(RUN)in complex optimization problems,the ERUN is proposed.The ERUN uses chaos opposition-based learning to improve the quality of the initial population,obtains a better individual update direction based on the quadratic interpolation method,and helps the population jump out of the local optimum through an adaptive t-distribution perturbation.The test results for the six benchmarks and objective functions demonstrate that ERUN has a faster convergence speed and higher solution accuracy than the three latest RUN variants.The obtained FHS is applied to a frequency-hopping system.The experimental results demonstrate that the Bit Error Rate(BER)of this method is approximately 4%in a fixed jamming environment and does not increase significantly in a changing jamming environment,demonstrating strong anti-jamming ability and complex environmental adaptability.

anti-jammingFrequency-Hopping Sequence(FHS)Runge-Kutta optimizer(RUN)quadratic interpolationadaptive t-distribution

张毅恒、刘以安、宋海凌

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江南大学人工智能与计算机学院,江苏无锡 214122

海军研究院 北京 100161

抗干扰 跳频序列 龙格库塔优化算法 二次插值 自适应t分布

国家自然科学基金江苏省自然科学基金

62076110BK20181341

2024

计算机工程
华东计算技术研究所 上海市计算机学会

计算机工程

CSTPCD北大核心
影响因子:0.581
ISSN:1000-3428
年,卷(期):2024.50(4)
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