• DocumentCode
    1796923
  • Title

    An effective doa estimation by exploring the spatial sparse representation of the inter-sensor data ratio model

  • Author

    Yuexian Zou ; Yifan Guo ; Weiqiao Zheng ; Ritz, C.H. ; Jiangtao Xi

  • Author_Institution
    Sch. of Electron. Comput. Eng., Peking Univ., Shenzhen, China
  • fYear
    2014
  • fDate
    9-13 July 2014
  • Firstpage
    42
  • Lastpage
    46
  • Abstract
    This paper investigates speaker direction of arrival (DOA) estimation using a single acoustic vector sensor (AVS). With the definition of the inter-sensor data ratio (ISDR) in the time-frequency (TF) domain and the use of the high local signal-to-noise ratio (HLSNR) TF points, an effective ISDR data model is derived, which determines the relationship between the ISDR and the AVS manifold vector. With the spatial sparse representation of the ISDR data, the DOA estimation is formulated by recovering the sparse matrix and locating the peak of the power spectrum of the reconstructed sparse matrix. Preliminary experimental results using simulations and real AVS recordings show that the proposed DOA estimation method is able to achieve high elevation and azimuth estimation accuracy for all angles when the SNR is above 10dB, avoiding the spatial aliasing problem and suppressing the adverse impact of the room reverberation. It is expected that the proposed DOA estimation method may find wide applications in portable devices due to its small compact physical size and superior performance.
  • Keywords
    acoustic signal processing; direction-of-arrival estimation; reverberation; signal reconstruction; signal representation; sparse matrices; speaker recognition; time-frequency analysis; AVS manifold vector; AVS recordings; HLSNR TF domain; ISDR data model; acoustic vector sensor; azimuth estimation; direction of arrival estimation; elevation estimation; high local signal-to-noise ratio; intersensor data ratio; portable devices; reconstructed sparse matrix recovery power spectrum; room reverberation; spatial aliasing problem; spatial sparse representation; speaker DOA estimation; time-frequency domain; Data models; Direction-of-arrival estimation; Estimation; Reverberation; Speech; Vectors; Direction of arrival estimation; acoustic vector sensor; inter-sensor data ratio; spatial sparse representation; time-frequency sparsity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (ChinaSIP), 2014 IEEE China Summit & International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4799-5401-8
  • Type

    conf

  • DOI
    10.1109/ChinaSIP.2014.6889198
  • Filename
    6889198