Burst Signal Sorting Based on the Phase Continuity

  • Fangmin Yan
  • Ming Li
  • Ling You
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 236)


This paper proposed a new algorithm for burst signal sorting. The proposed algorithm can be used to identify and locate TDMA users based on the continuity of carrier phase. In the proposed algorithm, the continuity of carrier phase between TDMA burst signals is evaluated according to their frequency deviations, initial phases and initial positions. Then burst signals are sorted based on their degree of continuity. The proposed algorithm is effective when researchers do not know the information which the burst carries. Some simulations and experiments in this paper show that the accurate rate of the proposed sorting algorithm is greater than 0.9 when the ES/N0 > 6 dB. Specially, and the performance is stable when the frequency deviation changes.


Burst signal sorting Phase continuity Carrier phase Frequency deviation Initial position 


  1. 1.
    Yu, Z., et al.: A multi-parameter synthetic signal sorting algorithm based on clustering. ICEMI ‘2007, vol. 2, pp. 363–366 (2007)Google Scholar
  2. 2.
    Guo, Q., et al.: A novel sorting method of radar signals based on support vector clustering and delaminating coupling. ICCI ’06, vol. 2, pp. 839–844 (2006)Google Scholar
  3. 3.
    Zhang, Y., Sun, G.: Application of radial basis function neural networks in complicated radar signal measurement and sorting. ICEMI’2007, vol. 3, pp. 375–378 (2007)Google Scholar
  4. 4.
    Huang, Y., Lu, Y.: Small carrier frequency difference detection based on the relative phase entropy. ISCIT 2007, pp 1417–1422 (2007)Google Scholar
  5. 5.
    Huang, Y.-l., et al.: Robust burst detection based on the average likelihood ratio test. J. Electron. Inf. Technol. 32(2), 345–349 (2010)CrossRefGoogle Scholar
  6. 6.
    Viterbi, A.J.: Principles of Coherent Communication. McGraw-Hill, New York (1966)Google Scholar
  7. 7.
    Morelli, M., Andrea, A.N.D., et al.: Feedforward ML-based timing estimation with PSK signals. IEEE Commun. Lett. 1, 80–82 (1997)Google Scholar
  8. 8.
    Noels, N., et al.: Carrier phase and frequency estimation for pilot-symbol assisted transmission: bounds and algorithms. IEEE Trans. Signal Process. 53, 4578–4587 (2005)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Erup, L., et al.: Interpolation in digital modems-part II: implementation and performance. IEEE Trans. Commun. 41, 998–1008 (1993)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Science and Technology on Blind Signal Processing LaboratoryChengduChina

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