The synchrosqueezing transform (SST) is an advanced post-processing method to sharpen the time–frequency representation (TFR). However, it still processes the signal in frequency domain. Therefore, it cannot effectively analyze signals whose energy is not well concentrated in frequency domain. The fractional S-transform (FrST) inherits the merits of the short-time fractional Fourier transform and the continuous wavelet transform, processing signals in fractional frequency domain. In this paper, a novel non-stationary signal processing tool, synchrosqueezing fractional S-transform (SSFrST) has been proposed, which combines the advantages of SST and FrST. First, we introduce a novel FrST and derive its fundamental properties. Second, based on the novel FrST, we propose SSFrST and discuss its reconstruction formula and implementation. It can not only improve time–frequency resolution, but also process signals in the time-fractional–frequency plane. Finally, we provide several applications to validate the effectiveness of our methods, including chirp signal parameters estimation, signal separation, filtering and noise separation.

同步压缩变换（SST）是一种先进的后处理方法，用于锐化时频表示（TFR）。然而，它仍然在频域中处理信号。因此，它无法有效地分析能量没有很好地集中在频域的信号。分数阶S变换（FrST）继承了短时分数阶傅里叶变换和连续小波变换的优点，在分数频域处理信号。本文提出了一种新颖的非平稳信号处理工具——同步压缩分数S变换（SSFrST），它结合了SST和FrST的优点。首先，我们介绍一种新颖的 FrST 并推导其基本属性。其次，基于新颖的FrST，我们提出了SSFrST并讨论了其重构公式和实现。它不仅可以提高时频分辨率，而且可以在时间-分数-频率平面上处理信号。最后，我们提供了几个应用来验证我们方法的有效性，包括线性调频信号参数估计、信号分离、滤波和噪声分离。