Gridless Sparsity-Based Localization for Near-Field Sources with Symmetric Linear Array
编号:71 访问权限:仅限参会人 更新:2020-08-05 10:17:00 浏览:433次 口头报告

报告开始:2020年06月08日 14:40(Asia/Shanghai)

报告时间:20min

所在会场:[S] Special Session [SS02] Sparse And Low-Rank Signal Processing For Array Processing And Wireless Communications

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摘要
In this paper, we investigate the problem of estimating the directions-of-arrival (DOAs) and ranges of multiple near-field narrowband sources impinging on a symmetric uniform linear array (ULA). By forming a Toeplitz-like correlation matrix from the anti-diagonal elements of the array covariance matrix, a convex optimization problem for the resultant Toeplitz-like matrix reconstruction is established and further a gridless sparsity-based localization for near-field sources is proposed. The DOAs can then be retrieved by using the recovered correlation matrix according to root-MUSIC or Vandermonde decomposition theorem. Additionally, the ranges are obtained through a subspace-based estimator with the corresponding estimated DOAs, while the association of the estimated DOAs and ranges are completed at the same time. Finally, the numerical examples are provided to substantiate the performance of our proposed method, and the simulation results demonstrate that the proposed method provides remarkable and satisfactory estimation performance.
关键词
Near-field; DOA estimation; source localization; Toeplitz covariance matrix; gridless method; uniform linear array
报告人
Weiliang Zuo
Xi'an Jiaotong University, China

稿件作者
Weiliang Zuo Xi'an Jiaotong University, China
Jingmin Xin Xi'an Jiaotong University, China
Tong Xiao Xi'an Jiaotong University, China
Nanning Zheng Xi'an Jiaotong University, China
Akira Sano Keio University, Japan
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重要日期
  • 会议日期

    06月08日

    2020

    06月11日

    2020

  • 01月12日 2020

    初稿截稿日期

  • 04月15日 2020

    提前注册日期

  • 12月31日 2020

    注册截止日期

主办单位
IEEE Signal Processing Society
承办单位
Zhejiang University
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