Mixed near-field and far-field source localization based on uniform linear array partition

Kai Wang, Ling Wang, Jing Rui Shang, Xiao Xia Qu

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

Abstract

Based on the polynomial decomposing method and high-order cumulant technique, a novel localization algorithm for the mixed near-field (NF) and far-field (FF) sources is proposed by using a uniform linear array (ULA). First, the ULA is divided into two sub-arrays, with different phase reference points. Three special fourth-order cumulant matrices are designed to eliminate the range parameters of the NF sources in the steering vectors, which only contain the direction of arrival (DOA) information. Second, based on the ESPRIT algorithm, the DOA of each source at the phase reference point is estimated. Third, with the DOA estimation, the type of the sources is classified by computing its coefficient matrix. Finally, the range parameters of NF sources and the DOAs of FF sources are captured. The proposed algorithm does not require any spectral search, which leads to low computational complexity. Moreover, this algorithm avoids the parameter matching procedure. Numerical experiments are conducted to verify the effectiveness of the proposed algorithm.

Original languageEnglish
Article number7552483
Pages (from-to)8083-8090
Number of pages8
JournalIEEE Sensors Journal
Volume16
Issue number22
DOIs
StatePublished - 15 Nov 2016

Keywords

  • Direction of arrival estimation
  • far-field sources
  • mixed sources
  • near-field sources
  • source localization

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