Passive localization of mixed Far-Field And Near-Field sources without estimating the number of sources

Jian Xie, Haihong Tao, Xuan Rao, Jia Su

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

This paper presents a novel algorithm for the localization of mixed far-field sources (FFSs) and near-field sources (NFSs) without estimating the source number. Firstly, the algorithm decouples the direction-of-arrival (DOA) estimation from the range estimation by exploiting fourth-order spatial-temporal cumulants of the observed data. Based on the joint diagonalization structure of multiple spatial-temporal cumulant matrices, a new one-dimensional (1-D) spatial spectrum function is derived to generate the DOA estimates of both FFSs and NFSs. Then, the FFSs and NFSs are identified and the range parameters of NFSs are determined via beamforming technique. Compared with traditional mixed sources localization algorithms, the proposed algorithm avoids the performance deterioration induced by erroneous source number estimation. Furthermore, it has a higher resolution capability and improves the estimation accuracy. Computer simulations are implemented to verify the effectiveness of the proposed algorithm.

Original languageEnglish
Pages (from-to)3834-3853
Number of pages20
JournalSensors
Volume15
Issue number2
DOIs
StatePublished - 6 Feb 2015
Externally publishedYes

Keywords

  • DOA estimation
  • Far-field
  • Fourth-order cumulants
  • Near-field
  • Range estimation
  • Sensor array signal processing
  • Source localization

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