A New Interpretation of S-Transform Spectrum: Phase Hopping Analysis and Estimation

ZHU Mingzhe; QI Yue; ZHANG Xinliang

doi:10.1049/cje.2019.01.010

Volume 28 Issue 2

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of Electronics > 2019 > 28(2): 338-343

ZHU Mingzhe, QI Yue, ZHANG Xinliang, “A New Interpretation of S-Transform Spectrum: Phase Hopping Analysis and Estimation,” Chinese Journal of Electronics, vol. 28, no. 2, pp. 338-343, 2019, doi: 10.1049/cje.2019.01.010

Citation:

ZHU Mingzhe, QI Yue, ZHANG Xinliang, “A New Interpretation of S-Transform Spectrum: Phase Hopping Analysis and Estimation,” Chinese Journal of Electronics, vol. 28, no. 2, pp. 338-343, 2019, doi: 10.1049/cje.2019.01.010

Citation:

PDF( 693 KB)

A New Interpretation of S-Transform Spectrum: Phase Hopping Analysis and Estimation

doi: 10.1049/cje.2019.01.010

School of Electronic Engineering, Xidian University, Xi'an 710071, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61701374).

Received Date: 2016-06-12
Rev Recd Date: 2017-12-04
Publish Date: 2019-03-10

Abstract

Abstract

S-Transform (ST) is a powerful timefrequency analysis tool with several useful performances. It has been found that ST is sensitive to the sudden change of signal phase and causes a spectrum spread phenomenon, which is often regarded as a shortage. However, a new interpretation of ST spectrum is proposed:the ST can provide a better property of phase hopping detection due to the sensitivity and mono-peak response of ST spectrum. It is a beneficial method to phase hopping estimation. The mathematical relation between the phase hopping angle and the instantaneous value changes of ST spectrum is derived in an explicit representation. This work helps to make a better understanding of the ST spectrum. Besides of the formula derivation, the characteristic is also proved and confirmed by the numerical simulations.
- S-Transform (ST),
- Phase hopping,
- Frequency spectrum spread

FullText(HTML)

References(16)

References

B. Yin, Y. He, B. Li, L. Zuo, and L. Yuan, “An adaptive SVD method for solving the Pass-Region problem in S-Transform time-frequency filters”, Chinese Journal of Electronics, Vol.24, No.1, pp.115-123, 2015.

F. Gao, X. Xue, J. Sun, J. Wang, and Y. Zhang, “A SAR image despeckling method based on two-dimensional STransform shrinkage”, IEEE Transactions on Geoscience and Remote Sensing, Vol.54, No.5, pp.3025-3034, 2016.

F. Gao, Y. Zhang, J. Wang, and J. Sun, “Fast algorithm for inverse two-dimensional S-Transform and Its application in time-frequency filtering for SAR image despeckling”, Chinese Journal of Electronics, Vol.25, No.1, pp.100-105, 2016.

X. Xu, X. Wu, X. Chen, and Z. Shen, “An instantaneous interference suppression approach based on S-Transform”, Acta Electronica Sinica, Vol.42, No.3, pp.602-606, 2014. (in Chinese)

S. Assous, A. Humeau, M. Tartas, P. Abraham, and J.P. L’ Huillier, “S-transform applied to laser doppler flowmetry reactive hyperemia signals”, Chinese Journal of Electronics, Vol.53, No.6, pp.1032-1037, 2006.

C.R. Pinnegar, H. Khosravani, and P. Federico, “Time-frequency phase analysis of ictal EEG recordings with the S-Transform”, IEEE Transactions on Biomedical Engineering, Vol.56, No.11, pp.2583-2593, 2009.

Z. Huang, J. Zhang, T. Zhao, and Y. Sun, “Synchrosqueezing S-Transform and its application in seismic spectral decomposition”, IEEE Transactions on Geoscience and Remote Sensing, Vol.54, No.2, pp.817-825, 2016.

M. Biswal, and P.K. Dash, “Measurement and classification of simultaneous power signal patterns with an S-Transform variant and fuzzy decision tree”, IEEE Transactions on Industrial Informatics, Vol.9, No.4, pp.1819-1827, 2013.

W. Yao, Q. Tang, Z. Teng, Y. Gao, and H. Wen, “Fast STransform for time-varying voltage flicker analysis”, IEEE Transactions on Instrumentation and Measurement, Vol.63, No.1, pp.72-79, 2014.

C.R. Pinnegar, and L. Mansinha, “The S-transform with windows of arbitrary and varying shape”, Geophysics, Vol.68, No.1, pp.381-385, 2003.

C.R. Pinnegar, and L. Mansinha, “The bi-Gaussian Stransform”, SIAM J. Sci. Comput, Vol.24, No.5, pp.1678-1692, 2003.

S. Ventosa, C. Simon, M. Schimmel, J.J. Danobeitia, and A. Manuel, “The S-Transform from a wavelet point of view”, IEEE Transactions on Signal Processing, Vol.56, No.7, pp.2771-2780, 2008.

E. Sejdic, L. Stankovic, M. Dakovic and J. Jiang, “Instantaneous frequency estimation using the S-Transform”, IEEE Signal Processing Letters, Vol.15, pp.309-312, 2008.

X. Zhang, Y. Qi, and M. Zhu, “Characteristic analysis of white Gaussian noise in S-Transformation domain”, Journal of Computer and Communications, Vol.2, No.2, pp.20-24, 2014.

X. Li, and Y. Wu, “Cross-term removal of WignerVille distribution for multi-component LFM signals”, Acta Electronica Sinica, Vol.45, No.2, pp.315-320, 2017. (in Chinese)

T. Thayaparan, L.J. Stankovic, C. Wernik and M. Dakovic, “Real-time motion compensation, image formation and image enhancement of moving targets in ISAR and SAR using Smethodbased approach”, IET Signal Processing, Vol.2, No.3, pp.247-264, 2008.

Relative Articles

Supplements(0)

Cited By

Proportional views