A novel FOTD-FRSET for optimization TFF analysis under impulsive noise

Impulsive noise is characterized by large amplitude and short duration, causing significant interference to the non-stationary signal representation and characteristic extraction. In response to the inadequacy of existing time-frequency analysis (TFA) methods in accurately representing the signal under impulsive noise, a novel time-fractional-frequency (TFF) analysis method based on FOTD-FRSET is proposed in this paper. This method effectively suppresses impulsive noise through fractional order tracking differentiator (FOTD), and then establishes the non-stationary signal TFF distribution by fractional synchroextraction transform (FRSET). Experimental results demonstrate that FOTD-FRSET can construct high-resolution TFF spectrum under impulsive noise, with superior energy concentration and ridge extraction over some existing methods. Furthermore, a noise correction algorithm is utilized to address the signal representation and characteristic extraction in the presence of non-standard symmetric α-stable distribution impulsive noise, enhancing the practicality of the proposed method for measured noise. Ultimately, the developed FOTD-FRSET method is effectively employed for linear frequency modulation (LFM) signal parameter estimation, and shows superior performance in the estimation accuracy, noise robustness, and practicality compared with existing methods.