Improved algorithm of fractional Fourier transform under condition of oversampling

For the weakness that Ozaktas sampling-type fractional Fourier transform (FRFT) has high computational complexity and low resolution, the computation of sampling-type FRFT is investigated under a condition of oversampling, and an improved algorithm of FRFT is presented. By reducing the value range of FRFT under the condition of oversampling, the frequency distribution in time-frequency plane is decreased and the discrete interval keeps the same as samples in time domain. Therefore, the interpolation is avoided and the computation is simplified significantly in the improved algorithm. Moreover, the improved algorithm is invertible. After further improvement, the algorithm has features with adjustable resolution, selectable output region and variable length of output data. The simulation results show the validity of the improved algorithm finally.