Matching Demodulation Transform and SynchroSqueezing in Time-Frequency Analysis

被引:247
|
作者
Wang, Shibin [1 ]
Chen, Xuefeng [1 ]
Cai, Gaigai [1 ]
Chen, Binqiang [1 ]
Li, Xiang [1 ]
He, Zhengjia [1 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Peoples R China
基金
高等学校博士学科点专项科研基金; 中国国家自然科学基金;
关键词
Time-frequency analysis; instantaneous frequency estimation; demodulation; synchrosqueezing; POLYNOMIAL FOURIER-TRANSFORM; INSTANTANEOUS FREQUENCY; SIGNAL ANALYSIS; PERFORMANCE; DISTRIBUTIONS; REASSIGNMENT; SPECTRUM; GEARBOX;
D O I
10.1109/TSP.2013.2276393
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The authors introduce an iterative algorithm, called matching demodulation transform (MDT), to generate a time-frequency (TF) representation with satisfactory energy concentration. As opposed to conventional TF analysis methods, this algorithm does not have to devise ad-hoc parametric TF dictionary. Assuming the FM law of a signal can be well characterized by a determined mathematical model with reasonable accuracy, the MDT algorithm can adopt a partial demodulation and stepwise refinement strategy for investigating TF properties of the signal. The practical implementation of the MDT involves an iterative procedure that gradually matches the true instantaneous frequency (IF) of the signal. Theoretical analysis of the MDT's performance is provided, including quantitative analysis of the IF estimation error and the convergence condition. Moreover, the MDT-based synchrosqueezing algorithm is described to further enhance the concentration and reduce the diffusion of the curved IF profile in the TF representation of original synchrosqueezing transform. The validity and practical utility of the proposed method are demonstrated by simulated as well as real signal.
引用
收藏
页码:69 / 84
页数:16
相关论文
共 50 条
  • [21] Nonlinear squeezing time-frequency transform for weak signal detection
    Wang, Shibin
    Chen, Xuefeng
    Wang, Yan
    Cai, Gaigai
    Ding, Baoqing
    Zhang, Xingwu
    SIGNAL PROCESSING, 2015, 113 : 195 - 210
  • [22] GNSS Code Multipath Time-Frequency Analysis Using Wavelet-Based Synchrosqueezing Transform in Urban Environments
    Dey, Abhijit
    Xu, Bing
    Lu, Xueyan
    Sharma, Nitin
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [23] Synchrosqueezing Transform Based on Frequency-Domain Gaussian-Modulated Linear Chirp Model for Seismic Time-Frequency Analysis
    Bing, Pingping
    Liu, Wei
    Zhang, Haoqi
    Zhu, Li
    Zhu, Guiping
    Zhou, Jun
    He, Binsheng
    MATHEMATICS, 2023, 11 (13)
  • [24] Second-Order Synchrosqueezing Transform or Invertible Reassignment? Towards Ideal Time-Frequency Representations
    Oberlin, Thomas
    Meignen, Sylvain
    Perrier, Valerie
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2015, 63 (05) : 1335 - 1344
  • [25] Iterative Synchrosqueezing-Based General Linear Chirplet Transform for Time-Frequency Feature Extraction
    Liu, Yi
    Xiang, Hang
    Jiang, Zhansi
    Xiang, Jiawei
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
  • [26] Multi-Synchrosqueezing Wavelet Transform for Time-Frequency Localization of Reservoir Characterization in Seismic Data
    Li, Zhen
    Sun, Fengyuan
    Gao, Jinghuai
    Liu, Naihao
    Wang, Zhiguo
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [27] Analysis of adaptive short-time Fourier transform-based synchrosqueezing transform
    Cai, Haiyan
    Jiang, Qingtang
    Li, Lin
    Suter, Bruce W.
    ANALYSIS AND APPLICATIONS, 2021, 19 (01) : 71 - 105
  • [28] Parameterized Resampling Time-Frequency Transform
    Li, Tianqi
    He, Qingbo
    Peng, Zhike
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2022, 70 : 5791 - 5805
  • [29] The Synchrosqueezing Algorithm Based on Generalized S-transform for High-Precision Time-Frequency Analysis
    Chen, Hui
    Lu, Lingqi
    Xu, Dan
    Kang, Jiaxing
    Chen, Xuping
    APPLIED SCIENCES-BASEL, 2017, 7 (08): : 769
  • [30] High-Resolution Seismic Time-Frequency Analysis Using the Synchrosqueezing Generalized S-Transform
    Wang, Qian
    Gao, Jinghuai
    Liu, Naihao
    Jiang, Xiudi
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2018, 15 (03) : 374 - 378