Extraction of Polyphase Modulation Parameters Using Cyclic Spectral Analysis

Abstract:

This paper presents an efficient algorithm to extract the polyphase modulation parameters from intercepted signals. The algorithm is essentially based on the cyclic spectral analysis method. A calculation of parameters extraction relative error as a function of different signal patterns reveals the performance of the algorithm, which is validated via simulation examples.

• Periodical: Applied Mechanics and Materials (Volumes 195-196)
• Pages: 186-190
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.195-196.186
• Online since: August 2012
• Authors: Xin Zhang, Feng Liu, Peng Zheng, Hui Fa Xu
• Keywords: Cyclic Spectral Analysis, Parameter Extraction, Polyphase Modulation

References

[1] P. E. Pace, Detecting and Classifying Low Probability of Intercept Radar, Norwood, MA: Horizon House Artech, (2004).

[2] P. D. Sutton, K. E. Nolan and L. E. Doyle, Cyclostationary Signatures in Practical Cognitive Radio Applications, Selected Areas in Communications, IEEE Journal on, vol. 26, pp.13-24, (2008).

DOI: 10.1109/jsac.2008.080103

[3] W. Jiandong, C. Tongwen and H. Biao, Cyclo-period estimation for discrete-time cyclo-stationary signals, Signal Processing, IEEE Transactions on, vol. 54, pp.83-94, (2006).

DOI: 10.1109/tsp.2005.859237

[4] K. -S. Lii and M. Rosenblatt, Estimation for almost periodic pro-cesses, Ann. Statist., vol. 34, no. 3, p.1115–1139, (2006).

[5] T. O. Gulum, P. E. Pace, Extraction of Polyphase Radra Modulation Parameters Using a Wigner-Ville Distribution-Radon Transform, IEEE International Conf. on Acoustics, Speech and Signal Processing, Las Vegas, NV, March (2008).

DOI: 10.1109/icassp.2008.4517907

[6] Gardner, W. A., Statistical Spectral Analysis: A Nonprobabilistic Theory, Prentice-Hall, Englewood Cliffs, NJ, (1987).

[7] R. S. Roberts, W. A. Brown and Jr. H. H. Loomis, Computationally efficient algorithms for cyclic spectral analysis, Signal Processing Magazine, IEEE, vol. 8, pp.38-49, (1991).

DOI: 10.1109/79.81008

[8] Gardner, W. A, Signal interception: A unifying theoretical framework for feature detection, IEEE Trans. on Communications, vol. 36, No. 8, pp.897-906, Aug. (1988).

DOI: 10.1109/26.3769

[9] Antonio F. Lima, Jr. Analysis of low probability of intercept radar signals using cyclostationary processing", Naval Postgraduate School Master, s thesis, Sept. (2002).

[10] T. O. Gulum, Autonomous Nonlinear Classification of LPI Radar Signal Modulations, Naval Postgraduate School Masters Thesis, Sept. (2007).

[11] Dobre O.A. Abdi. A, Bar-Ness.Y. Su, W. Survey of automatic modulation classification techniques: classical approaches and new trends, Communications, lET, volume 1, pp.137-156, (2007).

DOI: 10.1049/iet-com:20050176

[12] A. V. Dandawate and G. B. Giannakis, Asymptotic Theory of Mixed Time Averages and kth Order CyclicMoments and Cumulant Statistics, IEEE Trans. Inform. Theory, vol. 41, p.216–232, January (1995).

DOI: 10.1109/18.370106

[13] Antonio Napolitano, Discrete-Time Estimation of Second-Order Statistics of Generalized Almost-Cyclostationary Processes, IEEE Trans on signal processing, vol. 57, No. 5, May (2009).

DOI: 10.1109/tsp.2009.2013889

[14] A. Napolitano, On the spectral correlation measurement of non-stationary stochastic processes, in Proc. 2001 Signals, Systems and Computers, 2001. Conference Record of the Thirty-Fifth Asilomar Conference on, pp.898-902.

DOI: 10.1109/acssc.2001.987052