Aiming at the detection problem of hovering UAV in complex clutter environment, an improved Kalmus filterresidual echo timedomain mean cancelationadaptive CFAR joint processing algorithm is proposed to detect microDoppler of UAV and realize the purpose of air traffic control monitoring. The improved Kalmus filter is used for frequency domain filtering, and the high frequency signal and zero frequency signal of target echo are suppressed at the same time, and the micro Doppler signal gain near zero frequency is improved. The residual echo mean cancellation was used for secondary filtering to improve the signal to noise ratio of Doppler characteristic signals of the UAV highspeed rotor. The shorttime Fourier algorithm was used to detect Doppler changes in the target region. Finally, the constant false alarm processing was used to further suppress clutter and extract microDoppler information. The experimental results show that the proposed algorithm can effectively detect the rotor Doppler characteristics of hovering UAV, and the amplitude of the target Doppler signal is increased by about 20 dB to achieve the purpose of low altitude monitoring and control.