基于多尺度Chirplet稀疏分解和Wigner-Ville变换的时频分析方法

张天骐; 全盛荣; 强幸子; 江晓磊

doi:10.11999/JEIT160750

基于多尺度Chirplet稀疏分解和Wigner-Ville变换的时频分析方法

doi: 10.11999/JEIT160750

基金项目:

国家自然科学基金(61671095, 61371164, 61275099)，信号与信息处理重庆市市级重点实验室建设项目(CSTC2009 CA2003)，重庆市教育委员会科研项目(KJ130524, KJ1600427, KJ1600429)

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出版历程
- 收稿日期: 2016-07-14
- 修回日期: 2017-03-30
- 刊出日期: 2017-06-19

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

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)

摘要

摘要: 针对多分量多项式相位信号(mc-PPS)的Wigner-Ville分布存在的时频干扰问题，该文提出一种基于多尺度Chirplet稀疏分解和Wigner-Ville变换的时频分析方法。该方法采用多尺度的Chirplet基函数对信号进行投影分解，通过延时相关解调的分数阶傅里叶变换(FRFT)搜索投影系数最大的基函数，将搜索得到的基函数通过Wigner-Ville变换和最佳路径连接方法，逐次获得使分解信号能量最大的信号分量及其时频分布。仿真结果表明，该方法能在低信噪比条件下有效抑制等振幅mc-PPS的自交叉项和互交叉项的干扰，具有最佳的时频聚集性，克服了全局搜索基函数计算量大的问题，适用于非平稳信号的分析和处理。
- 多尺度Chirplet /
- Wigner-Ville变换 /
- 分数阶傅里叶变换 /
- 时频干扰 /
- 信噪比
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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