Canonical Correlation Analysis Using for DOA Estimation of Multiple Audio Sources

  • Gaoming Huang
  • Luxi Yang
  • Zhenya He
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3512)


In this paper we study direction of arrival (DOA) estimation of multiple audio sources by canonical correlation analysis (CCA), which is based on a sparse linear arrays. This array is composed of two separated subarrays. From the receiving data set, we can obtain the separate components by CCA. After a simple correlation, time difference can be obtained, and then we can compute the azimuth of different audio sources. The important contribution of this new estimation method is that it can reduce the effect of inter-sensor spacing to DOA estimation and the computation burden is light. Simulation result confirms the validity and practicality of the proposed approach. Results of DOA estimation are more accurate and stable based on this new method.


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  1. 1.
    Torkkola, K.: Blind separation of delayed sources based on information maximization. In: Proc. IEEE ICASSP, pp. 3509–3512 (1996)Google Scholar
  2. 2.
    Huang, G.M., Yang, L.X., He, Z.Y.: Time-Delay Direction Finding Based on Canonical Correlation Analysis. In: ISCAS 2005, Kobe, Japan, May 23-26 (2005) (accepted)Google Scholar
  3. 3.
    Hotelling, H.: Relations between two sets of variates. Biometrika (28), 321–377 (1936)Google Scholar
  4. 4.
    Anderson, T.W.: An Introduction to Multivariate Statistical Analysis, 2nd edn. John Wiley & Sons, Chichester (1984)MATHGoogle Scholar
  5. 5.
    Zhang, R.T., Fang, K.T.: An Introduction to Multivariate Statistical Analysis. Science House (1982)Google Scholar
  6. 6.
    Borga, M.: Learning Multidimensional Signal Processing. PhD thesis, Linköping University, Sweden, SE-581 83 Linköping, Sweden, 1998. Dissertation No 531, ISBN 91-7219-202-X (1998)Google Scholar
  7. 7.
    Bach, F.R., Jordan, M.I.: Kernel independent component analysis. Journal of Machine Learning Research (3), 1–48 (2002)Google Scholar
  8. 8.
    Fyfe, C., Lai, P.L.: Ica using kernel canonical correlation analysis. In: ICA 2000, vol. (8), pp. 279–284 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Gaoming Huang
    • 1
    • 2
  • Luxi Yang
    • 2
  • Zhenya He
    • 2
  1. 1.Naval University of EngineeringWuhanChina
  2. 2.Department of Radio EngineeringSoutheast UniversityNanjingChina

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