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The capability of a radar system to detect and identify the low-slow-small rotor unmanned aerial vehicle (UAV) is intensely important for management and control in low altitude, and it can be enhanced by the characteristics of UAV, which inherently carries micro-Doppler information. In this paper, we establish a micro-motion model of rotor UAV, and analyze the range walking and Doppler broadening caused by micro-motion. Hence, based on the characteristics of micro-Doppler of the rotors apart from the main body for the moving UAV, a micro-motion target detection and micro-Doppler parameters estimation method is proposed. Firstly, a method based on datashift in range dimension is used to compensate the translational component of the main body. Secondly, for the echo after translation compensation, a parameter estimation method of micro-Doppler based on the optimal demodulation operator is proposed. The operator contents the maximum likelihood criterion, which strengthens the difference between the micro-Doppler signal and the background clutters, so that more signal energy can be accumulated while the clutter is suppressed. Subsequently, the micro-Doppler parameters of the micro-motion component are obtained by the optimal demodulator, so that the detection and identification of the target are realized. Additionally, the performance of proposed method, including parameter estimation, signal-to-noise ratio (SNR) improvement and the calculation efficiency is analyzed. Finally, the simulation and experimental results reveal that the proposed method does possess the capability to improve the performance of detection and recognition of rotor UAV.INDEX TERMS Micro-Doppler, unmanned aerial vehicle (UAV) , optimal demodulation operator, micromotion parameter estimation, micro-motion target detection and identification