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

发布时间：2018-06-21 11:13

  本文选题：多尺度Chirplet + Wigner-Ville变换　； 参考：《电子与信息学报》2017年06期

【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。
[Abstract]:This paper presents a time-frequency analysis method based on multi-scale Chirplet sparse decomposition and Wigner-Ville transform to solve the time-frequency interference problem in the Wigner-Ville distribution of multi-component polynomial phase signals. In this method, the multi-scale Chirplet basis function is used to decompose the signal, and the fractional Fourier transform (FRFT) of delay correlation demodulation is used to search the basis function with the largest projection coefficient. Through the Wigner-Ville transform and the optimal path connection method, the signal components and their time-frequency distributions of the decomposed signal energy are obtained successively. The simulation results show that the proposed method can effectively suppress the interference of self-crossover and intercrossover terms of constant amplitude mc-PPS under the condition of low signal-to-noise ratio, and has the best time-frequency aggregation, and overcomes the problem of large computation of global search basis function. Suitable for non-stationary signal analysis and processing.
【作者单位】： 重庆邮电大学信号与信息处理重庆市重点实验室;
【基金】：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)~~
【分类号】：TN911.7
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本文编号：2048415