吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (2): 485-489.doi: 10.13229/j.cnki.jdxbgxb201402033

• 论文 • 上一篇    下一篇

基于阵列协方差矩阵列向量稀疏表示的高分辨波达方向估计

陈建, 田野, 孙晓颖   

  1. 吉林大学 通信工程学院, 长春 130022
  • 收稿日期:2013-02-20 出版日期:2014-02-01 发布日期:2014-02-01
  • 通讯作者: 田野(1985- ),男,博士研究生.研究方向:阵列信号处理,无线通信及应用.E-mail:tianfield@126.com E-mail:tianfield@126.com
  • 作者简介:陈建(1977- ),男,讲师,博士.研究方向:阵列信号处理,无线通信及应用.E-mail:chenjian@jlu.edu.cn
  • 基金资助:

    国家自然科学基金项目(61171137);高等学校博士学科点专项科研基金项目(20090061120042);吉林省科技发展计划项目(201201029).

High resolution direction-of-arrival estimation based on a sparse representation of array covariance matrix column vectors

CHEN Jian, TIAN Ye, SUN Xiao-ying   

  1. College of Communication and Engineering, Jilin University, Changchun 130022, China
  • Received:2013-02-20 Online:2014-02-01 Published:2014-02-01

摘要:

提出了两种基于稀疏重构的高分辨波达方向(DOA)估计方法。对空间进行粗、细两步网格划分,并在相应的过完备基下获得阵列协方差矩阵列向量的稀疏表示,分别基于剔除及差分处理抑制噪声干扰影响。采用lp范数约束正则化迭代加权最小范数(FOCUSS)算法进行稀疏重构,在重构过程中,对过完备基进行奇异值分解并剔除奇异值小于阈值项以减小计算量,并解决过完备基条件数过大带来的病态问题。仿真结果验证了所提算法的有效性和鲁棒性。

关键词: 通信技术, 波达方向, 稀疏重构, 过完备基, 奇异值分解

Abstract:

This paper presents two methods of high-resolution direction-of-arrival estimation based on signal sparse representation. First, a coarse-refined grid separation is created, which is used to structure the sparse representation of array covariance column vectors corresponding to overcomplete basis. Then, a removing and differencing method is employed to suppress the inference of noise. A regularized FOCUSS algorithm with lp norm constraint is applied for sparse reconstruction. Finally, the Singular Value Decomposition (SVD) is adopted to remove the singular value, which is less than the threshold to reduce complexity as well as ill-posed problem of overcomplete basis. Simulation results validate the effectiveness and robustness of the proposed method.

Key words: communication, direction of arrival (DOA), sparse reconstruction, overcomplete basis, singular value decomposition (SVD)

中图分类号: 

  • TN911.7

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