• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

MFSK Signal Individual Identification Algorithm Based on Bi-spectrum and Wavelet Analyses

Vol. 10, No.10, October 31, 2016
10.3837/tiis.2016.10.010, Download Paper (Free):

Abstract

Signal individual reconnaissance and identification is an extremely important research topic in non-cooperative domains such as electronic countermeasures and intelligence reconnaissance. Facing the characteristics of the complexity and changeability of current communication environment, how to realize radiation source signal individual identification under the low SNR conditions is an emphasis of research. A novel emitter individual identification method combined bi-spectrum analysis with wavelet feature is presented in this paper. It makes a feature fusion of bi-spectrum slice characteristics and energy variance characteristics of the secondary wavelet transform coefficient to identify MFSK signals under the low SNR (signal-to-noise ratios) environment. Theoretical analyses and computer simulation results show that the proposed algorithm has good recognition performance with the ability to suppress noise and interference, and reaches the recognition rate of more than 90% when the SNR is -6dB.


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Cite this article

[IEEE Style]
Fang Ye, Jie Chen, Yibing Li, and Juan Ge, "MFSK Signal Individual Identification Algorithm Based on Bi-spectrum and Wavelet Analyses," KSII Transactions on Internet and Information Systems, vol. 10, no. 10, pp. 4808-4824, 2016. DOI: 10.3837/tiis.2016.10.010

[ACM Style]
Ye, F., Chen, J., Li, Y., , , and Ge, J. 2016. MFSK Signal Individual Identification Algorithm Based on Bi-spectrum and Wavelet Analyses. KSII Transactions on Internet and Information Systems, 10, 10, (2016), 4808-4824. DOI: 10.3837/tiis.2016.10.010