Underdetermined direction of arrival estimation using acoustic vector sensor

Shengkui Zhao, Tigran Saluev, Douglas L. Jones

Research output: Contribution to journalArticlepeer-review


This paper presents a new approach for the estimation of two-dimensional (2D) direction-of-arrival (DOA) of more sources than sensors using an Acoustic Vector Sensor (AVS). The approach is developed based on Khatri-Rao (KR) product by exploiting the subspace characteristics of the time variant covariance matrices of the uncorrelated quasi-stationary source signals. An AVS is used to measure both the acoustic pressure and pressure gradients in a complete sound field and the DOAs are determined in both horizontal and vertical planes. The identifiability of the presented KR-AVS approach is studied in both theoretic analysis and computer simulations. Computer simulations demonstrated that 2D DOAs of six speech sources are successfully estimated. Superior root mean square error (RMSE) is obtained using the new KR-AVS array approach compared to the other geometries of the non-uniform linear array, the 2D L-shape array, and the 2D triangular array.

Original languageEnglish (US)
Pages (from-to)160-168
Number of pages9
JournalSignal Processing
StatePublished - Jul 1 2014


  • Covariance matrix
  • Direction of arrival estimation
  • Microphone arrays
  • Vector sensors

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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