王林,
韩红霞,
姬红兵,
江莉
西安电子科技大学电子工程学院 西安 710071
基金项目:国家自然基金项目(61803294)
详细信息
作者简介:李林:男,1980年生,博士,副教授,研究方向为雷达信号处理、信号检测与估值
王林:女,1995年生,硕士生,研究方向为非平稳信号处理
韩红霞:1991年生,硕士,研究方向为非平稳信号分离与时频分析
姬红兵:男,1963年生,博士,教授,研究方向为雷达信号处理、目标检测与跟踪
江莉:1982年生,博士,研究方向为非线性系统分析、振动信号处理
通讯作者:李林 lilin@xidian.edu.cn
中图分类号:TN911.7计量
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被引次数:0
出版历程
收稿日期:2019-03-13
修回日期:2019-05-27
网络出版日期:2019-08-23
刊出日期:2020-02-19
Research on the Adaptive Synchrosqueezing Algorithm
Lin LI,,Lin WANG,
Hongxia HAN,
Hongbing JI,
Li JIANG
School of Electronic Engineering, Xidian University, Xi’an 710071, China
Funds:The National Natural Science Foundation of China (61803294)
摘要
摘要:提高时频分辨率对多分量非平稳信号的分析与重建具有至关重要的作用。传统的时频分析方法由于窗口固定,分析频率变化较快的信号时存在时频聚集性不高的问题,无法自适应分辨多分量信号。该文针对频率快速变化信号,利用信号的局部信息特征,提出一种自适应的时频同步压缩变换算法。该方法有效提升了已有同步压缩变换时频分辨率,特别适用于频率接近且快速变换的多分量信号。同时,利用可分性条件,该文提出利用局部瑞利熵值对自适应窗口参数进行估计。最后,通过对合成信号和实测信号分析,证明了所提方法的可行性,对分析和重建复杂非平稳信号具有重要意义。
关键词:信号处理/
多分量信号/
时频分析/
同步压缩/
自适应窗口
Abstract:The improvement of time-frequency resolution plays a crucial role in the analysis and reconstruction of multi-component non-stationary signals. For traditional time-frequency analysis methods with fixed window, the time-frequency concentration is low and hardly to distinguish the multi-component signals with fast-varying frequencies. In this paper, by adopting the local information of the signal, an adaptive synchrosqueezing transform is proposed for the signals with fast-varying frequencies. The proposed method is with high time-frequency resolution, superior to existing synchrosqueezing methods, and particularly suitable for multi-component signals with close and fast-varying frequencies. Meanwhile, by using the separability condition, the adaptive window parameters are estimated by local Rényi entropy. Finally, experiments on synthetic and real signals demonstrate the correctness of the proposed method, which is suitable to analyze and recover complex non-stationary signals.
Key words:Signal processing/
Multi-component signal/
Time-frequency analysis/
SynchroSqueezing Transform (SST)/
Adaptive window
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