The “bird strike” and the “black flight” disturbance incident of the rotary-wing UAVs have become the “two hidden dangers” threatening the flight safety of civil aviation. The different countermeasures against birds and rotary-wing UAVs will be taken in the airports. The identification of birds and rotary-wing UAVs is of great significance for improving the monitoring performance of noncooperative targets and ensuring flight safety. Aiming at the problem that the discrimination performance of the rotor-wing UAV with strong maneuverability for the discrimination method based on the motion feature extraction is degraded, considering that the timefrequency spectrum of the bird target is more complex relative to the rotary-wing UAV. Firstly, the micro-motion features of the spectrum energy entropy corresponding to the target echo spectrum and the peak symmetry pair are constructed, Secondly, K-means is used to fuse the extracted motion features and micro-motion features and the identification of birds and rotor-wing UAV targets can be realized. The experimental results verify the effectiveness of the proposed method.