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Forty-Eight phase code design with good Merit Factor

机译:良好品质因数的四十八相代码设计

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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:改进遗传算法(MGA)被用作一种统计技术,用于获得组合优化问题的近似解。 MGA算法结合了两种算法的良好方法,例如遗传算法(GA)的全局最小收敛性和汉明扫描算法的快速收敛速度。在本文中,MGA被用于合成具有良好品质因数的48个相序。合成的序列具有复杂的信号结构,并且很难通过敌人的电子支援措施(ESM)进行检测和分析。

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