Floating Target Detection in Sea Clutter via Deshape Multiple Synchrosqueezing Transforms

The time-frequency analysis (TFA) method is an important technique to analyze the TF joint distribution of nonstationary signals. How to improve the performance of TF concentration and antinoise are the key research focuses of the TFA method. This article proposes the deshape multiple synchrosqueezi...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2024-08, Vol.60 (4), p.4285-4294
Main Authors: Guo, Juan, Hao, Guocheng, Yu, Jiantao, Wang, Pei, Bu, Laite, Yu, Zengyuan
Format: Article
Language:English
Subjects:
Antinoise performance
Cepstrum
floating target detection
Frequency modulation
Object detection
Shape
Signal resolution
Time-frequency analysis
time–frequency (TF) concentration
time–frequency analysis (TFA)
Transforms
Citations: Items that this one cites
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Summary:The time-frequency analysis (TFA) method is an important technique to analyze the TF joint distribution of nonstationary signals. How to improve the performance of TF concentration and antinoise are the key research focuses of the TFA method. This article proposes the deshape multiple synchrosqueezing transforms (DeMSSTs) to further improve the TF performance. The main principle is to apply the multiple synchrosqueezing transforms iteratively to deal with the result of the deshape synchrosqueezing transform by operations. In numerical simulation, the DeMSST method can better address multicomponent signals than other TFA methods, which demonstrates the performance of high concentration and strong antinoise. In the application analysis, the proposed DeMSST method can obtain a more accurate frequency curve and a clearer TF distribution of the ice multiparameter imaging X-band radar echo signal. It can be used to distinguish floating targets and sea clutter accurately.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2024.3373717