The short-time fractional Fourier transform (STFrFT) is beneficial for addressing non-stationary signals in many application settings. However, the STFrFT algorithm fails to obtain a high time–frequency (TF) concentration because of the uncertainty principle. To resolve these problems, we introduce a new algorithm that is referred to as the SSTFrFT, which is a combination of the synchroextracting transform and STFrFT. The main principle of this algorithm is to establish a synchroextracting operator based on the STFrFT and then to extract the TF coefficient of the ridgeline position in the TF distribution to improve the concentration. Using numerical simulations with two examples (linear frequency modulation signal and nonlinear frequency modulation signal), we illustrate how the algorithm can be useful in improving concentration. The instantaneous frequency estimation and energy distribution description are more accurate than traditional methods, such as the short-time Fourier transform, Wigner Ville distribution, synchrosqueezed transform, and STFrFT. Furthermore, we apply the algorithm to identify the frequency curve generated by the target’s motion from Ice Multiparameter Imaging X-Band radar echo data from the sea clutter background. The test results of the SSTFrFT method that we developed can accurately distinguish moving targets and sea clutter, which suggest the possible utility of this approach for detection and motion characteristics of marine moving targets.

短时分数阶傅立叶变换（STFrFT）对于解决许多应用场合中的非平稳信号很有用。但是，由于不确定性原理，STFrFT算法无法获得较高的时频（TF）浓度。为了解决这些问题，我们引入了一种称为SSTFrFT的新算法，该算法是同步提取变换和STFrFT的组合。该算法的主要原理是建立基于STFrFT的同步提取算子，然后提取TF分布中山脊线位置的TF系数以提高浓度。使用带有两个示例（线性频率调制信号和非线性频率调制信号）的数值模拟，我们说明了该算法如何在提高浓度方面有用。瞬时频率估计和能量分布描述比传统方法（例如短时傅立叶变换，Wigner Ville分布，同步压缩变换和STFrFT）更准确。此外，我们应用该算法从海杂波背景中的冰多参数成像X波段雷达回波数据中识别目标运动产生的频率曲线。我们开发的SSTFrFT方法的测试结果可以准确地区分运动目标和海浪杂波，这表明该方法对于检测海洋运动目标和运动特征可能具有实用性。此外，我们应用该算法从海杂波背景中的冰多参数成像X波段雷达回波数据中识别目标运动产生的频率曲线。我们开发的SSTFrFT方法的测试结果可以准确地区分运动目标和海浪杂波，这表明该方法对于检测海洋运动目标和运动特征可能具有实用性。此外，我们应用该算法从海杂波背景中的冰多参数成像X波段雷达回波数据中识别目标运动产生的频率曲线。我们开发的SSTFrFT方法的测试结果可以准确地区分运动目标和海浪杂波，这表明该方法对于检测海洋运动目标和运动特征可能具有实用性。