基于空间平滑差分的鲁棒自适应波束形成
DOI:
作者:
作者单位:

郑州大学 机械与动力工程学院 郑州 450001

作者简介:

通讯作者:

中图分类号:

TN98

基金项目:

国家自然科学基金(61873244);国家重点研究开发项目(2016YFF0203100);河南省重点科技攻关项目(202102210075)


Robust adaptive beamforming based on spatial smoothing difference algorithm
Author:
Affiliation:

School of Mechanical and Power Engineering, Zhengzhou University, Zhengzhou 450001, China

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对当采样协方差矩阵中包含期望信号时,模型失配会使MVDR(Minimum Variance Distortionless Response)自适应波束形成算法性能大幅下降的问题,本文提出一种基于空间平滑差分算法(Spatial Smoothing Difference Algorithm, SSDA)的鲁棒自适应波束形成算法。该算法首先通过空间平滑差分算法获得源数目先验知识,再对MVDR空间功率谱进行波峰搜索得到期望信号,最后再从采样协方差矩阵中去除期望信号协方差矩阵。仿真结果表明,在高信噪比输入的情况下,改进后的算法在去除期望信号后其输出信干噪比有了很大提升,比MVDR算法提高了2~3倍。

    Abstract:

    When the sampling covariance matrix contains the desired signal, the model mismatch will greatly reduce the performance of MVDR (minimum variance distortion response) adaptive beamforming algorithm. A robust adaptive beamforming algorithm based on spatial smoothing difference algorithm (SSDA) is proposed in this paper. The algorithm first obtains the prior knowledge of the number of sources through the spatial smoothing difference algorithm, then searches the wave crest of the MVDR spatial power spectrum to obtain the expected signal, and finally removes the expected signal covariance matrix from the sampling covariance matrix. The simulation results show that under the condition of high signal to noise ratio input, the output signal to interference plus noise ratio of the improved algorithm has been greatly improved after removing the expected signal, which is 2 ~ 3 times higher than that of MVDR algorithm.

    参考文献
    相似文献
    引证文献
引用本文

郝旺身,刘雨曦,冀科伟,张二亮,董辛旻,李继康,赵露露.基于空间平滑差分的鲁棒自适应波束形成[J].电子测量技术,2022,45(9):50-55

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2024-05-08
  • 出版日期: