DOA estimation for multiple sparse sources with arbitrarily arranged multiple sensors

Shoko Araki, Hiroshi Sawada, Ryo Mukai, Shoji Makino

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

Abstract

This paper proposes a method for estimating the direction of arrival (DOA) of multiple source signals for an underdetermined situation, where the number of sources N exceeds the number of sensors M (M<N). Some DOA estimation methods have already been proposed for underdetermined cases. However, since most of them restrict their microphone array arrangements, their DOA estimation ability is limited to a 2-dimensional plane. To deal with an underdetermined case where sources are distributed arbitrarily, we propose a method that can employ a 2- or 3-dimensional sensor array. Our new method employs the source sparseness assumption to handle an underdetermined case. Our formulation with the sensor coordinate vectors allows us to employ arbitrarily arranged sensors easily. We obtained promising experimental results for 2-dimensionally distributed sensors and sources 3×4, 3×5 (#sensors × #speech sources), and for 3-dimensional case with 4×5 in a room (reverberation time (RT) of 120 ms). We also investigate the DOA estimation performance under several reverberant conditions.

Original languageEnglish
Pages (from-to)265-275
Number of pages11
JournalJournal of Signal Processing Systems
Volume63
Issue number3
DOIs
Publication statusPublished - 2011 Jun
Externally publishedYes

Keywords

  • Anechoic model
  • Clustering
  • Direction of arrival (DOA)
  • Microphone array
  • Sparseness

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Signal Processing
  • Information Systems
  • Modelling and Simulation
  • Hardware and Architecture

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