Coprime Nested Arrays for DOA Estimation: Exploiting the Nesting Property of Coprime Array

Zhe Peng, Yingtao Ding, Shiwei Ren*, Haixia Wu, Weijiang Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

Recently, sparse arrays such as nested array and coprime array have attracted much attention in the field of array signal processing. In this letter, we develop a symmetric coprime array (SCA) whose sensor locations satisfy the nesting property, so it can be used as a dense subarray of nested array. Based on this observation, we propose a new sparse array named coprime nested array, which can achieve the same number of uniform degrees of freedom (uDOFs) as the prototype nested array, while the mutual coupling effect is at the same level as the coprime arrays. Moreover, an improved coprime nested array (ICNA) is proposed by rearranging some sensors in SCA to the right side of the sparse subarray. ICNA possesses more uDOFs than the existing nested arrays with further reduced mutual coupling effect. Numerical simulations verify the effectiveness of the proposed configurations.

Original languageEnglish
Pages (from-to)444-448
Number of pages5
JournalIEEE Signal Processing Letters
Volume29
DOIs
Publication statusPublished - 2022

Keywords

  • Array signal processing
  • Direction-of-arrival estimation
  • Estimation
  • Mutual coupling
  • Prototypes
  • Sensor arrays
  • Sparse matrices

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