An extended dimension music method for doa estimation of multiple real-valued sources

Li Liu, Jia Xu, Guan Wang, Xiang Gen Xia, Yang Gao, Teng Long

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

8 Citations (Scopus)

Abstract

The direction of arrival (DOA) estimation is a key issue in array signal processing, and the MUSIC algorithm is a kind of well-known DOA method. In this paper, an extended dimension MUSIC (ED-MUSIC) method is proposed for improving DOA estimation performance. For emitted real valued signals, the received array data is split into real and imaginary parts that are combined into a sampling vector of a virtual array with twice elements. It is found that the proposed ED-MUSIC outperforms the classical MUSIC in the DOA estimation performance and it can estimate 2M-1 real-valued sources, where M is the number of array elements. That is, ED-MUSIC is equivalent to doubling the element number as well as degree-of-freedom of an array. Finally, some numerical results are provided to demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2016 CIE International Conference on Radar, RADAR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509048281
DOIs
Publication statusPublished - 4 Oct 2017
Event2016 CIE International Conference on Radar, RADAR 2016 - Guangzhou, China
Duration: 10 Oct 201613 Oct 2016

Publication series

Name2016 CIE International Conference on Radar, RADAR 2016

Conference

Conference2016 CIE International Conference on Radar, RADAR 2016
Country/TerritoryChina
CityGuangzhou
Period10/10/1613/10/16

Keywords

  • Degree-of-freedom (DOF)
  • Direction of arrival (DOA)
  • Multiple signal classification (MUSIC) algorithm
  • Real-valued Source

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