Abstract: In an Alpha stable distribution noise environment, the traditional methods of digital modulation signals recognition have the problems of poor performance. A novel recognition method based on generalized fractional Fourier transform and fractional lower Wigner-Ville distribution is proposed to solve this problem. This method extracts the recognition characteristic parameters which are maximum of normalize and center instantaneous amplitude spectral density based on generalized fractional Fourier transform and maximum of fractional lower Wigner-Ville distribution amplitude. And then the method uses decision tree as a classifier to achieve digital modulation signals recognition. Simulation results show that the proposed method not only has better performance than the traditional recognition methods but also has higher recognition rate and good robustness in an Alpha stable distribution noise environment.