Uniaxial Acoustic Vector Sensors for direction-of-arrival estimation

Krishnaprasad Nambur Ramamohan*, Daniel Fernandez Comesaña, Geert Leus

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)
12 Downloads (Pure)

Abstract

In this paper, a specific reduced-channel Acoustic Vector Sensor (AVS) is proposed comprising one omni-directional microphone and only one particle velocity transducer, such that it can have an arbitrary orientation. Such a reduced transducer configuration is referred to as a Uniaxial AVS (U-AVS). The DOA performance of an array of U-AVSs is analyzed through its beampattern and compared to conventional configurations. It is shown that the U-AVS array beampattern results in an asymptotically biased estimate of the source location and it can be varied by choosing the orientation angles of the particle velocity transducers. Analytical expressions for the asymptotic bias of classical beamforming are proposed and verified both numerically as well as experimentally for Uniform Linear Arrays (ULAs). Furthermore, the Cramér-Rao Bound (CRB) and Mean Square Error (MSE) expressions are derived for a U-AVS array under a single source scenario and they are numerically evaluated for ULA. The implications of changing the orientations of the U-AVSs in the array on the MSE are discussed as well.

Original languageEnglish
Pages (from-to)276-291
Number of pages16
JournalJournal of Sound and Vibration
Volume437
DOIs
Publication statusPublished - 2018

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Acoustic Vector Sensor (AVS)
  • Array processing
  • Beampattern
  • Cramér-Rao Bound (CRB)
  • Direction-of-Arrival (DOA)
  • Mean Square Error (MSE)

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