Direction of arrival estimation using nested vector-sensor arrays via tensor modeling

Keyong Han, Arye Nehorai

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

3 Scopus citations

Abstract

We propose a new class of nested vector-sensor arrays, via tensor modeling, which is capable of increasing the number of degrees of freedom (DOFs) for direction-of-arrival (DOA) estimation, compared with the uniform linear array (ULA). By using one component's information of the interspectral tensor, the proposed nested vector-sensor array can provide O(N2) DOFs with only N physical sensors. To utilize the increased DOFs, a novel spatial smoothing approach is proposed, which preserves the data structure and avoids reorganization via tensor modeling. Further, we propose corresponding direction of arrival (DOA) estimation strategies. Based on the analytical results, we consider two main applications: electromagnetic (EM) vector sensors and acoustic vector sensors. We show that the DOA estimation performance is greatly improved due to the combination of the nested-array strategy and tensor modeling. The effectiveness of the proposed methods is verified through numerical examples.

Original languageEnglish
Title of host publication2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
PublisherIEEE Computer Society
Pages429-432
Number of pages4
ISBN (Print)9781479914814
DOIs
StatePublished - 2014
Event2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 - A Coruna, Spain
Duration: Jun 22 2014Jun 25 2014

Publication series

NameProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
ISSN (Electronic)2151-870X

Conference

Conference2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
Country/TerritorySpain
CityA Coruna
Period06/22/1406/25/14

Keywords

  • Direction of arrival estimation
  • acoustic vector sensors
  • electromagnetic vector sensors
  • nested array
  • tensor

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