The micro-Doppler signature is referred to as the unique signature of micro-motion target, which is significant for classification, recognition and imaging of special target. Because of the non-linear and non-stable characteristics of the special signal generated by micro-motion, in order to extract the micro-motion signature and provide a basis for target classification and identification, this thesis takes the object with rotating parts for example, under the single frequency system, to extract the micro-Doppler information based on the time-frequency analysis method. Then the micro-Doppler signature of micro-motion is obtained by simulation and verification, the transformation results and the differences of performance by using common time-frequency analysis tools are compared. The simulation testified that Gabor Transformation is feasible and stable in the aspect of extraction of micro-Doppler information, the remarkable potential of Gabor Transformation will provide a new approach of signature recognition for micro-motion target.