| 基于改进粒子群算法的自适应波束形成 |
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| 引用本文： | 程青青,李莉,周小平,刘桥.基于改进粒子群算法的自适应波束形成[J].上海师范大学学报(自然科学版),2018,47(2):151-155. |
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| 作者姓名： | 程青青 李莉 周小平 刘桥 |
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| 作者单位： | 上海师范大学信息与机电工程学院 |
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| 基金项目： | 上海市自然科学基金（16ZR1424500） |
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| 摘 要： | 基于最小均方误差准则,将自适应波束形成的权值求解问题表示为多目标优化模型,利用提出的改进粒子群优化算法,获得了阵列最优权值向量.改进粒子群优化算法中引入动态邻域拓扑结构,自适应调整粒子的领域搜索范围,避免粒子陷入局部最优.仿真结果表明:所提算法的收敛速度优于传统算法.
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| 关 键 词： | 自适应波束形成 粒子群算法 最小均方误差 多目标优化 |
| 收稿时间： | 2017/12/9 0:00:00 |
Adaptive beamforming based on improved particle swarm algorithm |
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| Cheng Qingqing,Li Li,Zhou Xiaoping and Liu Qiao.Adaptive beamforming based on improved particle swarm algorithm[J].Journal of Shanghai Normal University(Natural Sciences),2018,47(2):151-155. |
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| Authors: | Cheng Qingqing Li Li Zhou Xiaoping and Liu Qiao |
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| Affiliation: | The College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China,The College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China,The College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China and The College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China |
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| Abstract: | Based on minimum mean square error criterion,the problem of solving the weight of adaptive beamforming is represented as a multi-objective optimization model,and a proposed particle swarm optimization algorithm is used to obtain the optimal weight vector of the array.The improved particle swarm optimization algorithm introduces the dynamic neighborhood topological structure,and adaptively adjusts the domain search range of the particles to avoid the particles from falling into the local optimum.The simulation results showes that the convergence rate of the algorithm is better than the traditional algorithm. |
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| Keywords: | adaptive beamforming particle swarm algorithm minimum mean square error multi-objective optimization |
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