Skip to main content
placeholder image

Multisource DOA estimation based on time-frequency sparsity and joint inter-sensor data ratio with single acoustic vector sensor

Conference Paper


Abstract


  • By exploring the time-frequency (TF) sparsity property of the speech, the inter-sensor data ratios (ISDRs) of single acoustic vector sensor (AVS) have been derived and investigated. Under noiseless condition, ISDRs have favorable properties, such as being independent of frequency, DOA related with single valuedness, and no constraints on near or far field conditions. With these observations, we further investigated the behavior of ISDRs under noisy conditions and proposed a so-called ISDR-DOA estimation algorithm, where high local SNR data extraction and bivariate kernel density estimation techniques have been adopted to cluster the ISDRs representing the DOA information. Compared with the traditional DOA estimation methods with a small microphone array, the proposed algorithm has the merits of smaller size, no spatial aliasing and less computational cost. Simulation studies show that the proposed method with a single AVS can estimate up to seven sources simultaneously with high accuracy when the SNR is larger than 15dB. In addition, the DOA estimation results based on recorded data further validates the proposed algorithm.

Authors


  •   Zou, Yue-Xian (external author)
  •   Shi, Wenxing (external author)
  •   Li, Bo (external author)
  •   Ritz, Christian H.
  •   Shujau, Muawiyath (external author)
  •   Xi, Jiangtao

Publication Date


  • 2013

Citation


  • Y. X. Zou, W. Shi, B. Li, C. H. Ritz, M. Shujau & J. Xi, "Multisource DOA estimation based on time-frequency sparsity and joint inter-sensor data ratio with single acoustic vector sensor," in IEEE International Conference on Acoustics, Speech and Signal Processing, 2013, pp. 4011-4015.

Scopus Eid


  • 2-s2.0-84890490974

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1942

Start Page


  • 4011

End Page


  • 4015

Place Of Publication


  • http://www.icassp2013.com/

Abstract


  • By exploring the time-frequency (TF) sparsity property of the speech, the inter-sensor data ratios (ISDRs) of single acoustic vector sensor (AVS) have been derived and investigated. Under noiseless condition, ISDRs have favorable properties, such as being independent of frequency, DOA related with single valuedness, and no constraints on near or far field conditions. With these observations, we further investigated the behavior of ISDRs under noisy conditions and proposed a so-called ISDR-DOA estimation algorithm, where high local SNR data extraction and bivariate kernel density estimation techniques have been adopted to cluster the ISDRs representing the DOA information. Compared with the traditional DOA estimation methods with a small microphone array, the proposed algorithm has the merits of smaller size, no spatial aliasing and less computational cost. Simulation studies show that the proposed method with a single AVS can estimate up to seven sources simultaneously with high accuracy when the SNR is larger than 15dB. In addition, the DOA estimation results based on recorded data further validates the proposed algorithm.

Authors


  •   Zou, Yue-Xian (external author)
  •   Shi, Wenxing (external author)
  •   Li, Bo (external author)
  •   Ritz, Christian H.
  •   Shujau, Muawiyath (external author)
  •   Xi, Jiangtao

Publication Date


  • 2013

Citation


  • Y. X. Zou, W. Shi, B. Li, C. H. Ritz, M. Shujau & J. Xi, "Multisource DOA estimation based on time-frequency sparsity and joint inter-sensor data ratio with single acoustic vector sensor," in IEEE International Conference on Acoustics, Speech and Signal Processing, 2013, pp. 4011-4015.

Scopus Eid


  • 2-s2.0-84890490974

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1942

Start Page


  • 4011

End Page


  • 4015

Place Of Publication


  • http://www.icassp2013.com/