Abstract: In response to the urgent need for target recognition of flying birds and rotary-wing unmanned aerial vehicles (UAVs), micro-Doppler measurement experiments are carried out. Firstly, the flapping wing movement of flying birds, the main body movement of the rotary-wing UAV and the rotation of the rotor are modelled and characterized. Information from the radar moving target echo is extracted and the puller frequency shift information is then converted into a time-frequency map using short-time Fourier transform to finely describe the micro-Doppler characteristics of the target. The influencing factors of micro-Doppler characteristics are analyzed from multiple perspectives such as radar parameters, target types, and observation conditions. Micro-motion measurement experiments of flying birds and rotary-wing UAVs (MAVIC Air 2 and Inspire 2) are carried out using K-band chirp continuous wave radar to estimate micro-motion parameters, and the results verify the correctness of the theoretical model. The analysis of the measured data shows that the longer the target rotor blade length and the higher the speed, the higher the micro-Doppler frequency; the increase in the number of blades leads to the overlap of the micro-motion characteristics; the radar observation angle, modulation period and time window length of time-frequency analysis all have important influences on the micro-Doppler characteristics.