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DOA Estimation via SVD Denoising with Coprime Array Interpolation

  • School of Electronics and Information Engineering, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose a novel coprime array interpolation method for direction of arrival (DOA) estimation. By incorporating the Singular Value Decomposition (SVD) denoising algorithm, the proposed algorithm has the capability of suppressing the impact of noise. Through array interpolation, the sparse non-uniform coprime array is reconstructed to an uniform linear array (ULA) with the same aperture. Leveraging the ideal covariance matrix properties of the ULA, which includes Toeplitz matrix and Hermitian semi-definite priors, low-rank recovery is achieved using convex optimization techniques. Simulation results indicate that the proposed denoising DOA algorithm based on array interpolation outperforms in terms of degrees of freedom (DOF) and root-mean-square error (RMSE) of azimuth estimation.

Original languageEnglish
Title of host publicationISAP 2024 - International Symposium on Antennas and Propagation
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350364774
DOIs
StatePublished - 2024
Externally publishedYes
Event2024 International Symposium on Antennas and Propagation, ISAP 2024 - Incheon, Korea, Republic of
Duration: 5 Nov 20248 Nov 2024

Publication series

NameISAP 2024 - International Symposium on Antennas and Propagation

Conference

Conference2024 International Symposium on Antennas and Propagation, ISAP 2024
Country/TerritoryKorea, Republic of
CityIncheon
Period5/11/248/11/24

Keywords

  • DOA
  • SVD
  • Toeplitz matrix
  • coprime array
  • covariance matrix

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