# USE A NEURAL NETWORKS TO ESTIMATE AND TRACK THE PN SEQUENCE IN LOWER SNR DS-SS SIGNALS

### Tianqi Zhang, Shaosheng Dai, Zhengzhong Zhou, Xiaokang Lin

#### 2007

#### Abstract

This paper proposes a modified Sanger’s generalized Hebbian algorithm (GHA) neural network (NN) method to estimate and track the pseudo noise (PN) sequence in lower signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS) signals. The proposed method is based on eigen-analysis of DS-SS signals. The received signal is firstly sampled and divided into non-overlapping signal vectors according to a temporal window, which duration is a periods of PN sequence. Then an autocorrelation matrix is computed and accumulated by these signal vectors one by one. The PN sequence can be estimated and tracked by the principal eigenvector of autocorrelation matrix in the end. But the eigen-analysis method becomes inefficiency when the estimated PN sequence becomes longer or the estimated PN sequence becomes time varying. In order to overcome these shortcomings, we use a modified Sanger’s GHA NN to realize the PN sequence estimation and tracking from lower SNR input DS-SS signals adaptively and effectively.

#### References

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#### Paper Citation

#### in Harvard Style

Zhang T., Dai S., Zhou Z. and Lin X. (2007). **USE A NEURAL NETWORKS TO ESTIMATE AND TRACK THE PN SEQUENCE IN LOWER SNR DS-SS SIGNALS** . In *Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,* ISBN 978-972-8865-84-9, pages 379-384. DOI: 10.5220/0001647003790384

#### in Bibtex Style

@conference{icinco07,

author={Tianqi Zhang and Shaosheng Dai and Zhengzhong Zhou and Xiaokang Lin},

title={USE A NEURAL NETWORKS TO ESTIMATE AND TRACK THE PN SEQUENCE IN LOWER SNR DS-SS SIGNALS},

booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},

year={2007},

pages={379-384},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0001647003790384},

isbn={978-972-8865-84-9},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,

TI - USE A NEURAL NETWORKS TO ESTIMATE AND TRACK THE PN SEQUENCE IN LOWER SNR DS-SS SIGNALS

SN - 978-972-8865-84-9

AU - Zhang T.

AU - Dai S.

AU - Zhou Z.

AU - Lin X.

PY - 2007

SP - 379

EP - 384

DO - 10.5220/0001647003790384