Detection of the number of sources at low signal-to-noise ratio

Detection of the number of sources at low signal-to-noise ratio

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A new method to detect the number of sources in array signal processing is proposed. Most source detection techniques perform reasonably well at medium or high signal-to-noise ratio (SNR), but not at low SNR. This method exploits eigenvectors, instead of sample eigenvalues, for source enumeration. It employs the blind beamforming technique and the peak-to-average power ratio based frequency estimation algorithm to estimate the number of sources. Simulation results show that the proposed method is superior to the minimum description length and predictive description length algorithms at low SNR.


    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
      • E. Fishler , H. Messer . Order statistics approach for determining the number of sources using an array of sensors. IEEE Signal Process. Lett. , 4 , 179 - 182
    6. 6)
    7. 7)
    8. 8)
    9. 9)
      • D.W. Tufts , R. Kumaresan . Estimation of frequencies of multiple sinusoids: making linear predictionperform like maximum likelihood. Proc. IEEE , 9 , 975 - 989
    10. 10)
      • Dahanayake, B., Wong, K.: `Detection: a new approach [signals]', Proc. IEEE ICASSP, May 1988, p. 2773–2776.
    11. 11)
    12. 12)
    13. 13)
    14. 14)
      • B.G. Quinn , E. Hannan . (2001) The estimation and tracking of frequency.
    15. 15)
      • H.L. Van Trees . (2002) Optimum array processing. Part IV: Detection, estimation, and modulation theory.
    16. 16)
    17. 17)
      • T. Anderson . (2003) An introduction to multivariate statistical analysis.
    18. 18)
      • Hill, D.A., Bodie, J.B.: `Experimental carrier detection of BPSK and QPSK direct sequence spread spectrum signals', Conf. Rec. MILCOM'95, November 1995, p. 362–367.
    19. 19)
      • P. Stoica , R.L. Moses . (1997) Introduction to spectral analysis.
    20. 20)
      • A. Cichocki , S. Amari . (2002) Adaptive blind signal and image processing – learning algorithms and applications.

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