Multireassignment Method Based on S-Transform for Time-Frequency Analysis of Nonstationary Signal

Nonstationary signals, characterized by timevarying statistical properties, are prevalent across various disciplines, including telecommunications, seismology, mechanical engineering, and biomedical engineering. Traditional signal processing methods often face challenges in dealing with the spectral content variations and transient phenomena inherent to these signals. This article introduces a novel time-frequency analysis (TFA) method called the multireassignment S-transform (MRST), which is specifically designed to effectively characterize nonstationary signals. MRST builds upon the S-transform (ST) and integrates postprocessing strategies derived from the time-frequency multisqueezing transform, yielding a highly concentrated time-frequency representation (TFR) for signals with nonlinear harmonic and impulsive-like components. Simulated and experimental examples, including rub-impact fault data and electrocardiogram (ECG) signals, illustrate MRST’s superior performance in capturing transient features and providing accurate time-frequency localization. The results demonstrate that MRST is a powerful tool for analyzing complex nonstationary signals, offering high reconstruction accuracy and robustness in noisy environments.