Linear Canonical Transform Related Operators and Their Applications to Signal Analysis—Part II: Applications

WANG Xiaobo; ZHANG Qiliang; ZHOU You; QIAN Jing; ZOU Hongxing

doi:10.1049/cje.2015.04.014

Volume 24 Issue 2

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WANG Xiaobo, ZHANG Qiliang, ZHOU You, et al., “Linear Canonical Transform Related Operators and Their Applications to Signal Analysis—Part II: Applications,” Chinese Journal of Electronics, vol. 24, no. 2, pp. 312-316, 2015, doi: 10.1049/cje.2015.04.014

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WANG Xiaobo, ZHANG Qiliang, ZHOU You, et al., “Linear Canonical Transform Related Operators and Their Applications to Signal Analysis—Part II: Applications,” Chinese Journal of Electronics, vol. 24, no. 2, pp. 312-316, 2015, doi: 10.1049/cje.2015.04.014

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Linear Canonical Transform Related Operators and Their Applications to Signal Analysis—Part II: Applications

doi: 10.1049/cje.2015.04.014

1.
Department of Automation, Tsinghua University, Beijing 100084, China;
2.
Air Force Engineering University, Xi'an 710051, China

Funds: This work is supported by the National Natural Science Foundation of China (No.11301024, No.61071222).

More Information

Corresponding author: ZOU Hongxing is a professor at the Department of Automation, Tsinghua University, Beijing, China. His research interests include signal processing, pattern recognition and matrix factorization. (Email:Hongxing_Zou@tsinghua.edu.cn)
Publish Date: 2015-04-10

Abstract

Abstract

In this part of the paper, based on the fundamentals derived in Part I, we develop and implement two new algorithms. The first one, based on the proposed correlation operation for Linear canonical transform (LCT), is designed to detect and estimate linear Frequency modulated (FM) signals. The second one, based on the proposed joint canonical distribution, aims at reducing the cross-terms which are caused by the quadratic nature of Wigner distribution (WD). Several simulation results are given to illustrate both the strengths and weaknesses of the two algorithms.
- Autocorrelation operation,
- Chirp rate estimation,
- Reducing cross-terms

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References(11)

References

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