Detection of Weak Transient Electromagnetic Signals Based on Generalized Cross Correlation and Chaotic Time Series Prediction Integrate Algorithm

Zhang Yue; Liu Shang-he; Liu Wei-dong

doi:10.11999/JEIT 150306

Volume 37 Issue 11

Nov. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(11): 2769-2775

Zhang Yue, Liu Shang-he, Liu Wei-dong . Detection of Weak Transient Electromagnetic Signals Based on Generalized Cross Correlation and Chaotic Time Series Prediction Integrate Algorithm[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2769-2775. doi: 10.11999/JEIT 150306

Citation:

Zhang Yue, Liu Shang-he, Liu Wei-dong . Detection of Weak Transient Electromagnetic Signals Based on Generalized Cross Correlation and Chaotic Time Series Prediction Integrate Algorithm[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2769-2775. doi: 10.11999/JEIT 150306

Citation:

Zhang Yue, Liu Shang-he, Liu Wei-dong . Detection of Weak Transient Electromagnetic Signals Based on Generalized Cross Correlation and Chaotic Time Series Prediction Integrate Algorithm[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2769-2775. doi: 10.11999/JEIT 150306

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Detection of Weak Transient Electromagnetic Signals Based on Generalized Cross Correlation and Chaotic Time Series Prediction Integrate Algorithm

doi: 10.11999/JEIT 150306

Funds:

The National Natural Science Foundation of China (61172035)

Rev Recd Date: 2015-06-12
Publish Date: 2015-11-19

Abstract

Abstract

To investigate the remote detecting approaches of weak transient electromagnetic signals, the detecting method based on the general cross correlation and chaotic time series prediction integrate algorithm is proposed. Based on the double antennas test and cross correlation information estimation, the signal detection of weak non-periodic discharge signal in low Signal to Noise Ratio (SNR) is transformed to the estimation of periodic time- delay parameters, which decreases the level of noise simultaneously. The results of estimation are predicted based on chaotic predicting method, and the mean value of predicting error is the detection results of target signal. The feasibility of the approach is analyzed by simulating and experimental method. The results show that in the low SNR, the integration method can effectively restrain the interference from noise. Compared with the traditional cross correlation method or chaotic prediction algorithm, the detecting probability is higher for weak transient electromagnetic signals. Furthermore, the pulse integrating algorithm needs the less accumulation times, and its detecting efficiency increases. Hence, the proposed integrate algorithm is suitable for remote detection of partial discharge source.
- Signal detection,
- Transient electromagnetic,
- Weak signal,
- Generalized cross correlation,
- Chaos

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References(31)

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