一种改进的随机梯度恒模波束形成算法

Yuguo Wang, Zhongjin Zhang, Lufei He, Qi Zhong, Huaqiong Li
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引用次数: 1

摘要

分析了现有的SG-CMA递推公式,提出了一种收敛性更好、波束形成增益更强的改进SG-CMA。针对现有误差函数的缺点,对算法进行了改进。它以各单元的信号模量之和作为期望值,克服了信号模量的波动,增加了应用范围和抗噪能力。在建立任意阵列信号模量的基础上,对基于均匀线性阵列的SG-CMA和改进的SG-CMA进行了仿真比较。仿真结果验证了改进的SG-CMA的有效性,以及收敛性和波束形成增益的改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved stochastic gradient constant modulus beam-forming algorithm
This paper analyzes the existing recursion formulas of SG-CMA, presents an improved SG-CMA with better convergence and stronger beam-forming gain. Considering the disadvantages of existing error functions, the algorithm makes some changes. It takes the sum of the signal modulus of each element as the expected value, which overcomes the fluctuation of signal modulus, and increases the application range and anti-noise capability. The signal modulus of an arbitrary array is built, then the SG-CMA and the improved SG-CMA are compared by simulation based on uniform linear array. The simulation results verify the effectiveness of the improved SG-CMA as well as its improvement on convergence and beam-forming gain.
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