Wideband beamforming for multipath signals based on frequency invariant transformation

Regular Papers

Abstract

It is well known that the performance of conventional adaptive beamformers degrades severely due to the presence of coherent or correlated interferences (multipath propagation) and various techniques have been developed to improve the performance of the beamformer. However, most of the work in the past has been focused on the narrowband case. In this paper, the wideband beamforming problem in the presence of multipath signals is addressed, with a novel approach proposed by employing a pre-processing stage based on the frequency invariant beamforming (FIB) technique. In this approach, the received wideband array signals are first processed by an FIB network, and then a traditional narrowband adaptive beamformer or an appropriate instantaneous blind source separation (BSS) algorithm can be applied to the network outputs. It is shown that with the proposed structure, cancellation of the desired signal is reduced, leading to a significantly improved output signal to interference plus noise ratio (SINR).

Keywords

Wideband beamforming multipath signals frequency invariant beamforming blind beamforming convolutive mixtures 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    H. L. V. Trees. Optimum Array Processing, Part IV of Detection, Estimation, and Modulation Theory, New York, USA: John Wiley & Sons, 2002.Google Scholar
  2. [2]
    W. Liu, S. Weiss. Wideband Beamforming: Concepts and Techniques, Chichester, UK: John Wiley & Sons, 2010.CrossRefGoogle Scholar
  3. [3]
    S. Chen. Adaptive linear filtering design with minimum symbol error probability criterion. International Journal of Automation and Computing, vol. 3, no. 3, pp. 291–303, 2006.CrossRefGoogle Scholar
  4. [4]
    X. Hong, S. Chen. A minimum approximate-BER beamforming approach for PSK modulated wireless systems. International Journal of Automation and Computing, vol. 5, no. 3, pp. 284–289, 2008.MathSciNetCrossRefGoogle Scholar
  5. [5]
    S. Chen, W. Yao, L. Hanzo. Semi-blind adaptive beamforming for high-throughput quadrature amplitude modulation systems. International Journal of Automation and Computing, vol. 7, no. 4, pp. 565–570, 2010.CrossRefGoogle Scholar
  6. [6]
    V. U. Reddy, A. Paulraj, T. Kailath. Performance analysis of the optimum beamformer in the presence of correlated sources and its behavior under spatial smoothing. IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 35, no. 7, pp. 927–936, 1987.CrossRefGoogle Scholar
  7. [7]
    S. U. Pillai, B. H. Kwon. Forward/backward spatial smoothing techniques for coherent signal identification. IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, pp. 8–15, 1989.MATHCrossRefGoogle Scholar
  8. [8]
    K. C. Indukumar, V. U. Reddy. Broad-band DOA estimation and beamforming in multipath environment. In Proceedings of IEEE International Radar Conference, IEEE, Arlington, USA, pp. 532–537, 1990.CrossRefGoogle Scholar
  9. [9]
    E. Doron, M. A. Doron. Coherent wideband array processing. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, San Francisco, USA, vol. 2, pp. 497–500, 1992.Google Scholar
  10. [10]
    T. S. Lee. Efficient wideband source localization using beamforming invariance technique. IEEE Transactions on Signal Processing, vol. 42, no. 6, pp. 1376–1387, 1994.CrossRefGoogle Scholar
  11. [11]
    J. Krolik, D. Swingler. Focused wide-band array processing by spatial resampling. IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 38, no. 2, pp. 356–360, 1990.CrossRefGoogle Scholar
  12. [12]
    M. Zhang, M. H. Er. Robust adaptive beamforming for broadband arrays. Circuits Systems Signal Processing, vol. 16, no. 2, pp. 207–216, 1997.MATHCrossRefGoogle Scholar
  13. [13]
    E. D. D. Claudio. Optimal quiescent vectors for wideband ML beamforming in multipath fields. Signal Processing, vol. 85, pp. 107–120, 2005.MATHCrossRefGoogle Scholar
  14. [14]
    T. Sekiguchi, Y. Karasawa. Wideband beamspace adaptive array utilizing FIR fan filters for multi-beam forming. IEEE Transactions on Signal Processing, vol. 48, no. 1, pp. 277–284, 2000.CrossRefGoogle Scholar
  15. [15]
    W. Liu, S. Weiss, J. G. McWhirter, I. K. Proudler. Frequency invariant beamforming for two-dimensional and three-dimensional arrays. Signal Processing, vol. 87, no. 11, pp. 2535–2543, 2007.MATHCrossRefGoogle Scholar
  16. [16]
    W. Liu, S. Weiss. Broadband beamspace adaptive beamforming with spatial-only information. In Proceedings of IEEE Workshop on Sensor Array and Multichannel Signal Processing, IEEE, Darmstadt, Germany, pp. 330–334, 2008.CrossRefGoogle Scholar
  17. [17]
    S. Haykin. Unsupervised Adaptive Filtering, Volume 1: Blind Source Separation, New York, USA: John Wiley & Sons, 2000.Google Scholar
  18. [18]
    A. Cichocki, S. Amari. Adaptive Blind Signal and Image Processing, New York, USA: John Wiley & Sons, 2003.Google Scholar
  19. [19]
    J. F. Cardoso, A. Souloumiac. Blind beamforming for non-gaussian signals. IEE Proceedings F, Radar and Signal Processing, vol. 140, no. 6, pp. 362–370, 1993.CrossRefGoogle Scholar
  20. [20]
    E. Gonen, J. M. Mendel. Applications of cumulants to array processing. III. Blind beamforming for coherent signals. IEEE Transactions on Signal Processing, vol. 45, no. 9, pp. 2252–2264, 1997.CrossRefGoogle Scholar
  21. [21]
    J. Sheinvald. On blind beamforming for multiple non-gaussian signals and the constant-modulus algorithm. IEEE Transactions on Signal Processing, vol. 46, no. 7, pp. 1878–1885, 1998.CrossRefGoogle Scholar
  22. [22]
    K. Yang, T. Ohira, Y. Zhang, C. Y. Chi. Super-exponential blind adaptive beamforming. IEEE Transactions on Signal Processing, vol. 52, no. 6, pp. 1549–1563, 2004.CrossRefGoogle Scholar
  23. [23]
    X. Huang, H. C. Wu, J. E. Principe. Robust blind beamforming algorithm using joint multiple matrix diagonalization. IEEE Sensors Journal, vol. 7, no. 1, pp. 130–136, 2007.CrossRefGoogle Scholar
  24. [24]
    S. Chen, W. Yao, L. Hanzo. Semi-blind adaptive spatial equalisation for MIMO systems with high-order QAM signalling. IEEE Transactions on Wireless Communications, vol. 7, no. 11, pp. 4486–4491, 2008.CrossRefGoogle Scholar
  25. [25]
    W. Liu. Adaptive broadband beamforming with spatial-only information. In Proceedings of International Conference on Digital Signal Processing, IEEE, Cardiff, UK, pp. 575–578, 2007.CrossRefGoogle Scholar
  26. [26]
    W. Liu. Adaptive wideband beamforming with sensor delay-lines. Signal Processing, vol. 89, no. 5, pp. 876–882, 2009.MATHCrossRefGoogle Scholar
  27. [27]
    N. Lin, W. Liu, R. J. Langley. Performance analysis of an adaptive broadband beamformer based on a two-element linear array with sensor delay-line processing. Signal Processing, vol. 90, no. 1, pp. 269–281, 2010.MATHCrossRefGoogle Scholar
  28. [28]
    B. D. V. Veen, K. M. Buckley. Beamforming: A versatile approach to spatial filtering. IEEE Acoustics, Speech, and Signal Processing Magazine, vol. 5, no. 2, pp. 4–24, 1988.Google Scholar
  29. [29]
    E. D. D. Claudio, R. Parisi. Robust ML wideband beamforming in reverberant fields. IEEE Transactions on Signal Processing, vol. 51, no. 2, pp. 338–349, 2003.CrossRefGoogle Scholar
  30. [30]
    D. B. Ward, Z. Ding, R. A. Kennedy. Broadband DOA estimation using frequency invariant beamforming. IEEE Transactions on Signal Processing, vol. 46, pp. 1463–1469, 1998.CrossRefGoogle Scholar
  31. [31]
    D. H. Tuan, F. Demmel, P. Russer. A method for wideband direction-of-arrival estimation using frequency-domain frequency-invariant beamformers. In Proceedings of IEEE International Symposium on Antennas and Propagation, IEEE, Columbus, USA, vol. 3, pp. 244–247, 2003.Google Scholar
  32. [32]
    H. H. Chen, S. C. Chan. Adaptive beamforming and DOA estimation using uniform concentric spherical arrays with frequency invariant characteristics. Journal of VLSI Signal Processing, vol. 46, no. 1, pp. 15–34, 2007.CrossRefGoogle Scholar
  33. [33]
    H. H. Chen, S. C. Chan, K. L. Ho. Adaptive beamforming using frequency invariant uniform concentric circular arrays. IEEE Transactions on Circuits & Systems I: Regular Papers, vol. 54, no. 9, pp. 1938–1949, 2007.CrossRefGoogle Scholar
  34. [34]
    S. C. Chan, H. H. Chen. Uniform concentric circular arrays with frequency-invariant characteristics — Theory, design, adaptive beamforming and DOA estimation. IEEE Transactions on Signal Processing, vol. 55, no. 1, pp. 165–177, 2007.MathSciNetCrossRefGoogle Scholar
  35. [35]
    W. Liu, S. Weiss. Design of frequency invariant beamformers for broadband arrays. IEEE Transactions on Signal Processing, vol. 56, no. 2, pp. 855–860, 2008.MathSciNetCrossRefGoogle Scholar
  36. [36]
    W. Liu, D. McLernon, M. Ghogho. Design of frequency invariant beamformer without temporal filtering. IEEE Transactions on Signal Processing, vol. 57, no. 2, pp. 798–802, 2009.CrossRefGoogle Scholar
  37. [37]
    W. Liu, S. Weiss. Off-broadside main beam design and subband implementation for a class of frequency invariant beamformers. Signal Processing, vol. 89, no. 5, pp. 913–920, 2009.MATHCrossRefGoogle Scholar
  38. [38]
    Y. Zhao, W. Liu, R. J. Langley. Subband design of fixed wideband beamformers based on the least squares approach. Signal Processing, vol. 91, no. 4, pp. 1060–1065, 2011.MathSciNetMATHCrossRefGoogle Scholar
  39. [39]
    Y. Zhao, W. Liu, R. J. Langley. An application of the least squares approach to fixed beamformer design with frequency invariant constraints. IET Signal Processing, vol. 5, no. 3, pp. 281–291, 2011.CrossRefGoogle Scholar
  40. [40]
    W. Liu, R. Wu, R. Langley. Design and analysis of broadband beamspace adaptive arrays. IEEE Transactions on Antennas and Propagation, vol. 55, no. 12, pp. 3413–3420, 2007.CrossRefGoogle Scholar
  41. [41]
    S. Haykin. Unsupervised Adaptive Filtering, Volume 2: Blind Deconvolution, New York, USA: John Wiley & Sons, 2000.Google Scholar
  42. [42]
    B. W. Gillespie, H. S. Malvar, D. A. F. Florencio. Speech dereverberation via maximum-kurtosis subband adaptive filtering. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, Salt Lake City, USA, vol. 6, pp. 3701–3704, 2001.Google Scholar
  43. [43]
    W. Liu, D. P. Mandic. Semi-blind source separation for convolutive mixtures based on frequency invariant transformation. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, Philadelphia, USA, vol. 5, pp. 285–288, 2005.Google Scholar
  44. [44]
    W. Liu, D. P. Mandic. A normalised kurtosis based algorithm for blind source extraction from noisy measurements. Signal Processing, vol. 86, no. 7, pp. 1580–1585, 2006.MATHCrossRefGoogle Scholar

Copyright information

© Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Communications Research Group, Department of Electronic & Electrical EngineeringUniversity of SheffieldSheffieldUK

Personalised recommendations