Gridless Sparsity-Based Localization for Near-Field Sources with Symmetric Linear Array
ID:71 View Protection:ATTENDEE Updated Time:2020-08-05 10:17:00 Hits:452 Oral Presentation

Start Time:2020-06-08 14:40(Asia/Shanghai)

Duration:20min

Session:S Special Session » SS02Sparse And Low-Rank Signal Processing For Array Processing And Wireless Communications

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Abstract
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.
Keywords
Near-field; DOA estimation; source localization; Toeplitz covariance matrix; gridless method; uniform linear array
Speaker
Weiliang Zuo
Xi'an Jiaotong University, China

Submission Author
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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    Jun 08

    2020

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    Jun 11

    2020

  • Jan 12 2020

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  • Apr 15 2020

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