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Forty-Eight Phase Code design with good Merit Factor

机译:四十八个相位代码设计,具有良好的优点因素

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摘要

A Modified Genetic Algorithm (MGA) is used as a statistical technique for obtaining approximate solutions to combinatorial optimization problems. MGA algorithm combines the good methodologies of the two algorithms like global minimum converging property of Genetic Algorithm (GA) and fast convergence rate of Hamming scan algorithm. In this paper MGA is used to synthesize Forty-Eight phase sequences with good Merit Factor. The synthesized sequences have complex signal structure and very difficult to detect and analyze by an enemy's Electronic Support Measures (ESMs).
机译:改进的遗传算法(MGA)用作获得组合优化问题的近似解的统计技术。 MGA算法结合了遗传算法(GA)的全局最小融合特性等两种算法的良好方法,以及汉明扫描算法的快速收敛速率。在本文中,MGA用于合成具有良好优点因子的四十八相序列。合成序列具有复杂的信号结构,并且非常难以通过敌人的电子支持措施(ESMS)来检测和分析。

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