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  • 张小飞 ( 教授 )

    的个人主页 http://faculty.nuaa.edu.cn/xiaofeizhang/zh_CN/index.htm

  •   教授   博士生导师
  • 招生学科专业:
    信息与通信工程 -- 【招收博士、硕士研究生】 -- 电子信息工程学院
    信息与通信工程(集成电路设计) -- 【招收博士、硕士研究生】 -- 电子信息工程学院
    电子信息 -- 【招收博士、硕士研究生】 -- 电子信息工程学院
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Unfolded coprime L-shaped arrays for two-dimensional direction of arrival estimation

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所属单位:电子信息工程学院
发表刊物:INTERNATIONAL JOURNAL OF ELECTRONICS
关键字:DOA estimation L-shaped array MUSIC coprime array unfolded coprime array
摘要:Generally, a coprime L-shaped array (CLsA) is composed of two uniform L-shaped subarrays with larger spacing among inter-element to accomplish the improved direction of arrival (DOA) estimation performance. In this paper, the two subarrays are unfolded to extend the array aperture and the performance of the unfolded CLsA (UCLsA) for two-dimensional (2D) DOA estimation is investigated. In addition, an all array multiple signals classification (AA-MUSIC) algorithm is proposed for the UCLsA. By stacking the received signals of the two subarrays, the ambiguity problem can be avoided on the basis of the coprime property. Simultaneously, due to the combination of the cross-correlation and auto-correlation, the proposed AA-MUSIC algorithm can achieve the full degrees of freedom (DOFs) and obtain more accurate DOA estimates, nevertheless, the expensive total spectral search is entailed. Consequently, a reduced complexity MUSIC (RC-MUSIC) algorithm is proposed to relieve the computational burden. The Cramer-Rao Bounds (CRBs) are utilised as a theoretical benchmark for the lower bound of unbiased estimate. Furthermore, numerical simulations verify the effectiveness and superiority of the AA-MUSIC algorithm and RC-MUSIC method for the UCLsA.
ISSN号:0020-7217
是否译文:否
发表时间:2018-01-01
合写作者:弓盼,F70206593
通讯作者:张小飞

 

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