Time-frequency Analysis Method Based on Multi-scale Chirplet Sparse Decomposition and Wigner-Ville Transform

ZHANG Tianqi; QUAN Shengrong; QIANG Xingzi; JIANG Xiaolei

doi:10.11999/JEIT160750

Volume 39 Issue 6

Jun. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(6): 1333-1339

ZHANG Tianqi, QUAN Shengrong, QIANG Xingzi, JIANG Xiaolei. Time-frequency Analysis Method Based on Multi-scale Chirplet Sparse Decomposition and Wigner-Ville Transform[J]. Journal of Electronics & Information Technology, 2017, 39(6): 1333-1339. doi: 10.11999/JEIT160750

Citation:

ZHANG Tianqi, QUAN Shengrong, QIANG Xingzi, JIANG Xiaolei. Time-frequency Analysis Method Based on Multi-scale Chirplet Sparse Decomposition and Wigner-Ville Transform[J]. Journal of Electronics & Information Technology, 2017, 39(6): 1333-1339. doi: 10.11999/JEIT160750

Citation:

ZHANG Tianqi, QUAN Shengrong, QIANG Xingzi, JIANG Xiaolei. Time-frequency Analysis Method Based on Multi-scale Chirplet Sparse Decomposition and Wigner-Ville Transform[J]. Journal of Electronics & Information Technology, 2017, 39(6): 1333-1339. doi: 10.11999/JEIT160750

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Time-frequency Analysis Method Based on Multi-scale Chirplet Sparse Decomposition and Wigner-Ville Transform

doi: 10.11999/JEIT160750

Funds:

The National Natural Science Foundation of China (61671095, 61371164, 61275099), The Project of Key Laboratory of Signal and Information Processing of Chongqing (CSTC2009CA2003), The Research Project of Chongqing Educational Commission (KJ130524, KJ1600427, KJ1600429)

Received Date: 2016-07-14
Rev Recd Date: 2017-03-30
Publish Date: 2017-06-19

Abstract

Abstract

To solve the problem of time-frequency interference existing in the multicomponent Polynomial Phase Signal (mc-PPS) Wigner-Ville distribution, a new time-frequency analysis method based on the multi-scale Chirplet sparse decomposition and Wigner-Ville transform is proposed. This method projects mc-PPS onto the multi-scale Chirplet base functions, searching best base functions by the improved FRactional Fourier Transform (FRFT). Through the Wigner-Ville transform and best path pursuit algorithm, the base functions constitute largest energy signals component and power distribution in turns. Simulation results verify that the proposed method can restrain effectively the cross-interference of constant mc-PPS in low Signal-to-Noise Ratio condition, maintain a high time-frequency aggregation, and overcome the large computation of global searching algorithm. Furthermore, this method is suitable for non-stationary signals analysis and processing.
- Multi-scale Chirplet,
- Wigner-Ville transform,
- FRactional Fourier Transform (FRFT),
- Time-frequency interference,
- Signal-to-Noise Ratio

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References(21)

References

张贤达. 非平稳信号分析与处理[M]. 北京: 国防工业出版社, 2001: 451-492.

ZHANG Xianda. Nonstationary Signal Analysis and Processing[M]. Beijing: National Defence Industry Press, 2001: 451-492.

邹红星, 周小波, 李衍达. 时频分析: 回溯与前瞻[J]. 电子学报, 2000, 28(8): 78-84.

ZOU Hongxing, ZHOU Xiaobo, and LI Yanda. Which time- frequency analysisa survey[J]. Acta Electronica Sinica, 2000, 28(8): 78-84.

KRISTIAN T and MARC M. Adaptive time-frequency analysis for noise reduction in an audio filter bank with low delay[J]. IEEE/ACM Transactions on Audio, Speech and Language Processing, 2016, 24(4): 784-795. doi: 10.1109/ TASLP.2016.2526779.

MISHRA A, SINGH A K, and SAHU S. ECG signal denoising using time-frequency based filtering approach[C]. Proceedings of the International Conference on Communication and Signal Processing, India, 2016: 0503-0507. doi: 10.1109/ICCSP.2016.7754188.

WANG J and HE Q. Wavelet packet envelope manifold for fault diagnosis of rolling element bearings[J]. IEEE Transactions on Instrumentation and Measurement, 2016, 65(11): 2515-2526. doi: 10.1109/TIM.2016.2566838.

刘颖, 陈殿仁, 陈磊, 等. 基于周期Choi-Williams Hough变换的线性调频连续波信号参数估计算法[J]. 电子与信息学报, 2015, 37(5): 1135-1140. doi: 10.11999/JEIT140876.

LIU Ying, CHEN Dianren, CHEN Lei, et al. Parameters estimation algorithm of linear frequency modulated continuous wave signals based on period Choi-Williams Hough transform[J]. Journal of Electronics Information Technology, 2015, 37(5): 1135-1140. doi: 10.11999/JEIT 140876.

王忠仁, 林君, 李文伟. 基于Wigner-Ville分布的复杂时变信号的时频分析[J]. 电子学报, 2005, 33(12): 2239-2241.

WANG Zhongren, LIN Jun, and LI Wenwei. Time-frequency analysis for complex time-varying signals based on Wigner- Ville distribution[J]. Acta Electronica Sinica, 2005, 33(12): 2239-2241.

王勇, 姜义成. 多项式Wigner-Ville分布的频域卷积实现[J]. 电子与信息学报, 2008, 30(2): 286-289.

WANG Yong and JIANG Yicheng. Realization of polynomial Wigner-Ville distribution based on the convolution in frequency domain[J]. Journal of Electronics Information Technology, 2008, 30(2): 286-289.

PENG H W, CHANG H T, and LIN C C. 2-D linear frequency modulation signal separation using fractional Fourier transform[C]. Proceedings of the International Symposium on Computer, Consumer and Control, Taibei, China, 2016: 755-758. doi: 10.1109/IS3C.2016.193.

CANDS E J, CHARLTON P, and HELGASON H. Detecting highly oscillatory signals by chirplet path pursuit[J]. Applied and Computational Harmonic Analysis, 2008, 24(1): 14-40.

罗洁思, 于德介, 彭富强. 基于多尺度线调频基信号稀疏分解的多分量LFM信号检测[J]. 电子与信息学报, 2009, 31(11) 2781-2785.

LUO Jiesi, YU Dejie, and PENG Fuqiang. Multicomponent LFM signals detection based on multi-scale Chirplet sparse signal decomposition[J]. Journal of Electronics Information Technology, 2009, 31(11): 2781-2785.

梅检民, 肖云魁, 周斌, 等. 基于FRFT的改进多尺度线调频基稀疏信号分解方法[J]. 振动工程学报, 2013, 26(1): 135-142.

MEI Jianmin, XIAO Yunkui, ZHOU Bin, et al. Improved multi-scale chirplet sparse signal decomposition method based on fractional Fourier transform[J]. Journal of Vibration Engineering, 2013, 26(1): 135-142.

刘渝. 快速解线性调频信号估计[J]. 数据采集与处理, 1999, 14(2): 175-178.

LIU Yu. Fast dechirp algorithm[J]. Journal of Data Acquisition Processing, 1999, 14(2): 175-178.

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