Blind Estimation of Pseudo-random Noise Codes in NPLSC-DSSS Signals Based on Goodness of Fit Test

ZHAO Zhijin; QIANG Fangfang; LI Miao; SHEN Lei; WANG Haiquan

doi:10.11999/JEIT160541

Volume 39 Issue 3

Mar. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(3): 749-753

ZHAO Zhijin, QIANG Fangfang, LI Miao, SHEN Lei, WANG Haiquan . Blind Estimation of Pseudo-random Noise Codes in NPLSC-DSSS Signals Based on Goodness of Fit Test[J]. Journal of Electronics & Information Technology, 2017, 39(3): 749-753. doi: 10.11999/JEIT160541

Citation:

ZHAO Zhijin, QIANG Fangfang, LI Miao, SHEN Lei, WANG Haiquan . Blind Estimation of Pseudo-random Noise Codes in NPLSC-DSSS Signals Based on Goodness of Fit Test[J]. Journal of Electronics & Information Technology, 2017, 39(3): 749-753. doi: 10.11999/JEIT160541

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Blind Estimation of Pseudo-random Noise Codes in NPLSC-DSSS Signals Based on Goodness of Fit Test

doi: 10.11999/JEIT160541

Funds:

The National Natural Science Foundation of China (61571172)

Received Date: 2016-05-06
Rev Recd Date: 2016-10-31
Publish Date: 2017-03-19

Abstract

Abstract

For blind estimation of Pseudo-random Noise (PN) codes in Non-Periodic Long and Short Codes Direct Sequence Spread Spectrum (NPLSC-DSSS) signals, the Triple Correlation Function (TCF) common peak theory of m-sequence and probability function of NPLSC-DSSS signals TCF estimate are given firstly. Then sequences of TCF peaks are built with their conjugate sets features, binary hypothesis test model and accurate detection algorithm of TCF common peaks using goodness of fit test are proposed. Meanwhile, many false peaks are eliminated to improve the estimation performance using the property of forward and backward TCF peaks and cumulative-sums increasing trend of TCF peaks in conjugate sets. Lastly, the primitive polynomials of long and short pseudo-random codes can be estimated with the matrixs oblique elementary method. Simulations show that the proposed method can effectively estimate the PN codes of NPLSC-DSSS signal at low Signal-to-Noise Ratio (SNR).

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References(26)

References

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