Your browser doesn't support javascript.
loading
An Improved Synchrosqueezing S-Transform and Its Application in a GPR Detection Task.
Xiong, Hongqiang; An, Baizhou; Sun, Boyang; Lu, Jiayu.
Afiliação
  • Xiong H; College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China.
  • An B; Ningxia Geophysical and Geochemical Exploration Institute (Autonomous Regional Deep Earth Exploration Center), Yinchuan 750001, China.
  • Sun B; Ningxia Geophysical and Geochemical Exploration Institute (Autonomous Regional Deep Earth Exploration Center), Yinchuan 750001, China.
  • Lu J; School of Resource and Geosciences, China University of Mining and Technology, Xuzhou 221000, China.
Sensors (Basel) ; 24(10)2024 May 08.
Article em En | MEDLINE | ID: mdl-38793836
ABSTRACT
The S-transform is a fundamental time-frequency (T-F) domain analysis method in ground penetrating radar (GPR) data processing and can be used for identifying targets, denoising, extracting thin layers, and high-resolution imaging. However, the S-transform spectrum experiences energy leakage near the instantaneous frequency. This phenomenon causes frequency components to erroneously spread over a wider range, impacting the accuracy and precision of GPR data processing. Synchrosqueezing is an effective method to prevent spectrum leakage. In this work, we introduce the synchrosqueezing generalized phase-shifting S-transform (SS-GPST). Initially, it resolves the compatibility issue between the S-transform and the synchrosqueezing strategy through phase-shifting. Subsequently, the SS-GPST accomplishes spectral energy focusing and resolution enhancement via a generalized parameter and synchrosqueezing. A synthetic signal test shows that the SS-GPST excels over other methods at focusing degree, spectral resolution, and signal reconstruction accuracy and speed. In actual GPR tunnel detection data processing, we assess the adaptability of the SS-GPST from three aspects spectral energy distribution, thin layer identification, and data denoising. The results indicate (1) compared to other methods, the SS-GPST accurately expresses spectral components with a strong focusing degree and fewer interference components; (2) high-frequency slices of the SS-GPST accurately detect the top and bottom interfaces of a 3.0-3.5 cm reinforcement protection layer; and (3) due to fewer interference components in the SS-GPST spectrum, reconstructing GPR profiles through the SS-GPST inverse transform is an efficient denoising technique. The SS-GPST demonstrates adaptability to different data processing purposes, offers high-resolution T-F spectra, and shows potential to supersede the S-transform.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article