A Blind Recognition Method of Binary Pseudo-random Sequence

ZHANG Tianqi; ZHAO Liang; ZHANG Ting; YANG Kai

doi:10.11999/JEIT170552

Volume 40 Issue 2

Feb. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(2): 394-399

ZHANG Tianqi, ZHAO Liang, ZHANG Ting, YANG Kai. A Blind Recognition Method of Binary Pseudo-random Sequence[J]. Journal of Electronics & Information Technology, 2018, 40(2): 394-399. doi: 10.11999/JEIT170552

Citation:

ZHANG Tianqi, ZHAO Liang, ZHANG Ting, YANG Kai. A Blind Recognition Method of Binary Pseudo-random Sequence[J]. Journal of Electronics & Information Technology, 2018, 40(2): 394-399. doi: 10.11999/JEIT170552

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A Blind Recognition Method of Binary Pseudo-random Sequence

doi: 10.11999/JEIT170552

Funds:

The National Natural Science Foundation of China (61671095, 61371164), The Project of Key Laboratory of Signal and Information Processing of Chongqing (CSTC2009 CA2003), The Research Project of Chongqing Educational Commission (KJ130524, KJ1600427, KJ1600429)

Received Date: 2017-06-08
Rev Recd Date: 2017-08-29
Publish Date: 2018-02-19

Abstract

Abstract

For the generator polynomial blind recognition method of binary pseudo-random sequences, it is necessary to know the polynomials order in advance, the algorithm with poor fault tolerance and high complexity. In this paper, the analysis matrix is first constructed according to the estimated polynomials order of the intercepted sequence. Then the method of Galoisian column Gaussian elimination is used to identify the order of the polynomial of the intercept sequence. Finally, the equation set is constructed according to the polynomials order. In order to reduce the complexity of the algorithm, the polynomials that satisfy the equations in the finite polynomial library are the generator polynomials of the intercepted sequences. The simulation results show that the proposed method can distinguish the m sequence, the Gold sequence, or other binary pseudorandom sequences, and effectively identify their own generating polynomials, and has good fault tolerance.
- Pseudo-random sequence,
- Column Gaussian elimination,
- Match search,
- Generator polynomial

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References(26)

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