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首页> 外文期刊>Mathematical Problems in Engineering >Application of Bee Evolutionary Genetic Algorithm to Maximum Likelihood Direction-of-Arrival Estimation
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Application of Bee Evolutionary Genetic Algorithm to Maximum Likelihood Direction-of-Arrival Estimation

机译：Bee进化遗传算法在最大似然到达方向估计中的应用

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摘要

The maximum likelihood (ML) method achieves an excellent performance for DOA estimation. However, its computational complexity is too high for a multidimensional nonlinear solution search. To address this issue, an improved bee evolutionary genetic algorithm (IBEGA) is applied to maximize the likelihood function for DOA estimation. First, an opposition-based reinforcement learning method is utilized to achieve a better initial population for the BEGA. Second, an improved arithmetic crossover operator is proposed to improve the global searching performance. The experimental results show that the proposed algorithm can reduce the computational complexity of ML DOA estimation significantly without sacrificing the estimation accuracy.
机译：最大似然（ML）方法在DOA估计中具有出色的性能。但是，对于多维非线性解搜索而言，其计算复杂度过高。为了解决这个问题，一种改进的蜜蜂进化遗传算法（IBEGA）被应用来最大化DOA估计的似然函数。首先，基于对立的强化学习方法被用来为BEGA获得更好的初始填充。其次，提出了一种改进的算术交叉算子，以提高全局搜索性能。实验结果表明，该算法可以在不牺牲估计精度的前提下，显着降低ML DOA估计的计算复杂度。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第5期|6035870.1-6035870.11|共11页
  • 作者

    Fan Xinnan; Pang Linbin; Shi Pengfei; Li Guangzhi; Zhang Xuewu;

  • 作者单位

    Hohai Univ, Coll IOT Engn, Changzhou 213022, Peoples R China|Jiangsu Prov Collaborat Innovat Ctr World Water V, Nanjing 211100, Jiangsu, Peoples R China;

    Hohai Univ, Coll IOT Engn, Changzhou 213022, Peoples R China|Hohai Univ, Coll Comp & Informat, Nanjing 211100, Jiangsu, Peoples R China;

    Hohai Univ, Coll IOT Engn, Changzhou 213022, Peoples R China;

    Hohai Univ, Coll IOT Engn, Changzhou 213022, Peoples R China;

    Hohai Univ, Coll IOT Engn, Changzhou 213022, Peoples R China;

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