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| Time-frequency Analysis Method Based on Multi-scale Chirplet Sparse Decomposition and Wigner-Ville Transform |
| ZHANG Tianqi QUAN Shengrong QIANG Xingzi JIANG Xiaolei |
| (Chongqing Key Laboratory of Signal and Information Processing, Chongqing University of Posts and Telecommunications, Chongqing 400065, China) |
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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.
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Received: 14 July 2016
Published: 25 April 2017
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| Fund: 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) |
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Corresponding Authors:
QUAN Shengrong
E-mail: srquancqupt@163.com
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