Reduced Dimensional 2-D DOA Estimation via Least Partial Search with Automatic Pairing
编号:166 访问权限:仅限参会人 更新:2020-08-05 10:17:28 浏览:442次 口头报告

报告开始:2020年06月08日 14:00(Asia/Shanghai)

报告时间:20min

所在会场:[S] Special Session [SS16] Sparse Array Configuration For Improved Spectrum Estimation And Its Applications

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摘要
In this paper, we address the problem of two dimensional (2-D) direction-of-arrival (DOA) estimation for parallel co-prime arrays. Traditional 2-D DOA estimation methods usually suffer from the tremendous computation burden caused by spectral search and angle pairing. To this end, in this paper we propose an efficient reduced dimensional least spectral search based estimation method with automatic pairing. Specifically, we first utilize the cross-covariance matrix to decouple the 2-D DOA estimation problem into a one-dimensional (1-D) one, and then design a least spectral search based 1-D DOA estimation method according to the relations between true and ambiguous angles. Finally, we estimate the remaining 1-D DOAs via least square criterion with automatic pairing. We evaluate the complexity and present the simulation results to show the effectiveness of the proposed method.
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报告人
Fenggang Sun
Shandong Agricultural University, China

稿件作者
Fenggang Sun Shandong Agricultural University, China
Shengqi Ouyang North China Electric Power University, China
Peng Lan Shandong Agricultural University, China
Fengdi Li Shandong Agricultural University, China
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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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