DOA Estimation Method Using Sparse Representation with Orthogonal Projection

Fujia Xu, Aifei Liu*, Shiqi Mo, Song Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

In order to reduce the effect of noises on DOA estimation, this paper proposes a direction-of-arrival (DOA) estimation method using sparse representation with orthogonal projection (OPSR). The OPSR method obtains a new covariance matrix by projecting the covariance matrix of the array data to the signal subspace, leading to the elimination of the noise subspace. Afterwards, based on the new covariance matrix after the orthogonal projection, a new sparse representation model is established and employed for DOA estimation. Simulation results demonstrate that compared to other methods, the OPSR method has higher angle resolution and better DOA estimation performance in the cases of few snapshots and low SNRs.

Original languageEnglish
Pages (from-to)397-402
Number of pages6
JournalJournal of Beijing Institute of Technology (English Edition)
Volume30
Issue number4
DOIs
Publication statusPublished - Dec 2021
Externally publishedYes

Keywords

  • DOA estimation
  • Orthogonal projection
  • Signal subspace
  • Sparse representation

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