Multi-rotor drones are increasingly becoming a threat to critical facilities while bringing convenience. This article focuses on the difficulty of tracking and detecting low slow small unmanned aerial vehicles （UAVs）， and develops a UAV tracking， detection， recognition， and positioning system based on microphone array sound source localization. The system acquires UAV noise signals in real time， and then uses a wavelet transform-based beamforming time-frequency sound source localization algorithm for UAV noise source localization， and finally integrates the position of the multi-rotor UAV obtained by inversion of the microphone array and the image captured by the video. Tests conducted in a fully anechoic room have shown that the positioning system can accurately track the lateral flight and up-and-down flight of drones， accurately detect the position of drones even in blind spots of cameras， and effectively compensate for video detection. And the positioning accuracy of the system is 92.2%， which is better than that of similar systems.