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兵工学报 ›› 2015, Vol. 36 ›› Issue (2): 294-298.doi: 10.3969/j.issn.1000-1093.2015.02.015

• 论文 • 上一篇    下一篇

互耦效应下一种基于实值稀疏表示的波达方向估计算法

吴振1, 戴继生1,2, 朱湘临1, 赵德安1   

  1. (1.江苏大学 电气信息工程学院江苏 镇江 212013;2.东南大学 移动通信国家重点实验室江苏 南京 210096)
  • 收稿日期:2013-09-27 修回日期:2013-09-27 上线日期:2015-04-07
  • 作者简介:吴振(1990—)男硕士研究生
  • 基金资助:
    国家自然科学基金项目(61102054); 东南大学移动通信国家重点实验室开放研究基金项目(2013D08)

A Real-valued Sparse Representation Method for DOA Estimation with Unknown Mutual Coupling

WU Zhen1, DAI Ji-sheng1,2, ZHU Xiang-lin1, ZHAO De-an1   

  1. (1.School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, Jiangsu, China;2National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, Jiangsu, China)
  • Received:2013-09-27 Revised:2013-09-27 Online:2015-04-07

摘要: 针对未知互耦条件下的波达方向(DOA)估计问题,提出了一种未知互耦条件下基于实值稀疏表示的加权子空间DOA估计算法。新算法利用一个特定的酉变换矩阵,将一个复杂的复值优化问题转化为一个实值优化问题,从而有效地将原问题的计算复杂度减少4倍以上。此外,为了进一步提高稀疏表示的估计算法估计精度,在原有l1 范数优化模型基础上引入一个能使得DOA估计方差取得最小值的最优子空间加权矩阵。仿真实验表明,在低信噪比情况下,新算法能进一步提高稀疏表示的估计算法抗噪能力,获得更好的估计精度。

关键词: 信息处理技术, 波达方向估计, 稀疏表示, 互耦, 均匀线阵

Abstract: The paper presents a real-valued sparse representation method for DOA estimation in the presence of unknown mutual coupling. Utilizing a certain unitary transformation and taking advantage of the special structure of mutual coupling matrix (MCM) for uniform linear arrays (ULAs), we are able to convert complex-valued manifold matrices of ULAs with unknown mutual coupling into real ones. Due to this transformation, the computational complexity can be decreased by a factor of at least four. Moreover, the proposed method is expected to have a better noise suppression, as it exploits an additional optimal weighting matrix. Thus, the proposed method outperforms the original one, especially when signal-to-noise ratio (SNR) is low. Simulation results verify the efficiency of the proposed method.

Key words: information processing technology, direction of arrival estimation, sparse representation, mutual coupling, uniform linear array

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