Parameter Estimation of the Direct Sequence Spread Spectrum Signal Based on Time-Smoothing Cyclic Periodogram

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Abstract:

The direct sequence spread spectrum (DS-SS) signal is a typical kind of LPI signals widely-used in the modern digital communication system, and it is difficult to be detected for its statistical characteristic similar to noise. An algorithm for estimating the code rate, carrier frequency of DS-SS signals was proposed using time-smoothing cyclic periodogram instead of cyclic spectrum according to cyclostationary feature of DS-SS signal to improve the precision of parameter estimation. The estimation performance was analyzed for the cyclic spectrum by time-smoothing cyclic periodogram from the tapering points in the case of limited data length. Simulation results showed that the proposed algorithm is effective.

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181-185

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August 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Shen Yunchun. The technique of spectrum spreading[M]. National Defence iIndustry Press,1995-07, pp.13-15(in Chinese).

Google Scholar

[2] Zhao Xiaolin, Xu Jiantai. The Detection of BPSK-DS signal based on cycle spectrum[J]. Information Technology, 2004, 28(8): 3032(in Chinese).

Google Scholar

[3] Vucic Desimir, Obradovic Milorad. Spectral Correlationo PSK Signals [A]. Telecommunications in Modern Satellite Cableand Broadcasting Services, (1999).

DOI: 10.1109/telsks.1999.804744

Google Scholar

[4] MaWenjie, YangShiming, RenWu, etal. Spectral Correlation Function in Low SNR Environment[A]. Radio Science Conference, 2004: 197200.

Google Scholar

[5] Brown W.A., Loomis H., Jr. Digital implementations of spectral correlation analyzers. IEEE Trans. Signal Processing, 1993, 4(2), pp.703-720.

DOI: 10.1109/78.193211

Google Scholar

[6] R.S. Roberts, W.A. Brown and H.H. Loomis, Jr., computionally efficient algorithms for cyclic spectral analyis, IEEE Signal Processing, 1991, 8(2), pp.38-49.

DOI: 10.1109/79.81008

Google Scholar

[7] Gao Yulong. Modulation Recognition and High Dynamic Synchronization Based On Cyclic Spectral Density. Harbin institute of technology. 2007. p.38.

Google Scholar