北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2014, Vol. 37 ›› Issue (5): 105-108.doi: 10.13190/j.jbupt.2014.05.022

• 研究报告 • 上一篇    下一篇

一种快速收敛的自适应波束形成算法

赵季红1,2, 张瑞卿1, 曲桦1   

  1. 1. 西安交通大学 电子与信息工程学院, 西安 710049;
    2. 西安邮电大学 通信与信息工程学院, 西安 710061
  • 收稿日期:2013-11-18 出版日期:2014-10-28 发布日期:2014-11-07
  • 作者简介:赵季红(1963- ), 女, 教授, 博士生导师, E-mail: zhaojihong@mail.xjtu.edu.cn.
  • 基金资助:

    国家自然科学基金项目(61372092);国家无线重大专项项目(2013ZX03002010-003);国家高技术研究发展计划项目(2014AA01A701)

Adaptive Beamforming Algorithm with Fast Convergence Speed

ZHAO Ji-hong1,2, ZHANG Rui-qing1, QU Hua1   

  1. 1. School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China;
    2. School of Telecommunications and Information Engineering, Xi'an University of Posts ann Telecommunications, Xi'an 710061, China
  • Received:2013-11-18 Online:2014-10-28 Published:2014-11-07

摘要:

为了解决传统最小均方(LMS)自适应波束形成算法在低信噪比环境下收敛速度较慢的问题,提出了一种快速收敛的小波域自适应波束形成算法. 该算法利用小波变换软阈值法消除信号中的加性高斯白噪声,并在此基础上将牛顿法应用于LMS算法中,提高了小波域LMS算法的收敛速度. 仿真结果表明,相比传统LMS算法,在低信噪比环境下,该算法收敛速度加快,稳态误差减小,波束形成精确度有较大的提高;同时相对于已有的小波域LMS算法,该算法的收敛速度和精度也有所提高.

关键词: 自适应波束形成, 小波变换, 牛顿法

Abstract:

The conventional least mean square (LMS) based adaptive beamforming converges very slowly under low signal-to-noise ratio (SNR), thus an adaptive beamforming algorithm in wavelet domain with a fast convergence rate was put forward. The white Gaussian noise could be erased by means of wavelet transform soft-threshold method. Besides, Newton's method was further applied in LMS algorithm for beamforming in wavelet domain. Simulation shows that the proposed algorithm indeed improve the convergence accuracy and the convergence rate compared with either the conventional LMS algorithm or the existed LMS algorithm in wavelet domain. It also substantially improves the accuracy of beamforming compared with the conventional LMS algorithm.

Key words: adaptive beamforming, wavelet transform, Newton's method

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