Local maximum multisynchrosqueezing transform and its application

被引:1
|
作者
Tu, Qiyu [1 ]
Sheng, Zhichao [1 ]
Fang, Yong [1 ]
Nasir, Ali Arshad [2 ,3 ]
机构
[1] Shanghai Univ, Key Lab Specialty Fiber Opt & Opt Access Networks, Shanghai 200444, Peoples R China
[2] King Fahd Univ Petr & Minerals, Dept Elect Engn, Dhahran 31261, Saudi Arabia
[3] King Fahd Univ Petr & Minerals, Ctr Commun Syst & Sensing, Dhahran 31261, Saudi Arabia
基金
中国国家自然科学基金;
关键词
Time-frequency analysis; Synchrosqueezing transform; Strongly time-varying signal; Micro -Doppler signals; EMPIRICAL MODE DECOMPOSITION; TIME-FREQUENCY ANALYSIS; SYNCHROSQUEEZING TRANSFORM; REASSIGNMENT; ALGORITHM; SIGNALS;
D O I
10.1016/j.dsp.2023.104122
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 synchrosqueezing technique is widely used for analyzing the time variations of non-stationary signals. Recently, the local maximum synchrosqueezing transform (LMSST) method has been presented to effectively improve the time-frequency (TF) representation, which seems to be a promising tool. However, the LMSST is unable to accurately characterize the amplitude of strongly non-stationary signals, making it rather challenging to extract accurate TF information for signals with strong frequency modulation. Therefore, there is a significant barrier preventing the development of more precise and sharper results from the micro-Doppler signals with strong frequency modulation and multi-component characteristics. To overcome this problem, we coined a novel LMSST method, namely local maximum multisynchrosqueezing transform (LMMSST). The LMMSST is on the basis of local maximizing TF reassignment and multiple synchrosqueezing operators in which an iterated redistribution program is used to concentrate the ambiguous TF energy with a stepwise approach. As a result, the LMMSST significantly enhances the concentration in terms of energy of TF results and performs better in addressing strong frequency modulation and multi-component signals. In addition, it also allows perfect signal reconstruction and accurate estimating of the instantaneous frequency. Numerical results and application cases verify the effectiveness of the LMMSST method. & COPY; 2023 Elsevier Inc. All rights reserved.
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页数:11
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