Reduced Dimensional 2-D DOA Estimation via Least Partial Search with Automatic Pairing
ID:166 View Protection:ATTENDEE Updated Time:2020-08-05 10:17:28 Hits:375 Oral Presentation

Start Time:2020-06-08 14:00(Asia/Shanghai)

Duration:20min

Session:S Special Session » SS16Sparse Array Configuration For Improved Spectrum Estimation And Its Applications

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Abstract
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.
Keywords
Speaker
Fenggang Sun
Shandong Agricultural University, China

Submission Author
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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  • Conference Date

    Jun 08

    2020

    to

    Jun 11

    2020

  • Jan 12 2020

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  • Apr 15 2020

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  • Dec 31 2020

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