Research On Feature Extraction Method Of Bistatic Radar For Multi-rotor UAV

The detection and recognition of multi-rotor UAVs is currently a hot issue in the radar industry.Monostatic radar is currently a relatively common method.However,because the multi-rotor UAV monostatic radar scattering interface(RCS)is small,there are obstructions and line-of-sights.Constraints and other issues,the practical application of monostatic radar is faced with problems such as limited operating range.The bistatic/multistatic radar,which is a typical representative of the external source radar,can solve the airspace coverage due to its space diversity advantage,and enhance the bistatic RCS in some directions,providing another option for the detection and identification of multi-rotor UAVs.At present,the bistatic scattering characteristics of multi-rotor UAVs,especially the characteristics of the micro-motion information generated by the rotation of the UAV’s rotor in the bistatic radar observation mode,are still unclear.Research has been carried out in three aspects: base RCS,bistatic micro-Doppler,motion and structural feature extraction.The main tasks are as follows::(1)The multi-rotor UAV bistatic radar echo model was established,and the airspace distribution characteristics of the multi-rotor UAV bistatic RCS were analyzed through electromagnetic calculation and darkroom measurement data,and the bistatic angle,the number of rotors,the number of blades,and the initial position of the blades were revealed.The influence of parameters such as speed,speed,etc.on bistatic micro-Doppler,and the conclusions obtained provide an effective reference for the optimal deployment of bistatic/multistatic radar detection and identification of multi-rotor UAVs.(2)A behavior identification method for multi-rotor drones based on micro-Doppler features is proposed.Based on the joint simulation of FEKO and MATLAB,the problem of the lack of dynamic echo data of the bistatic radar multi-rotor UAV is solved.Through electromagnetic simulation data,the hovering,forward/backward,ascent/descent,The bistatic micro-Doppler features in flight modes such as rotation and side flight reveal the inherent differences in bistatic micro-Doppler features in different flight modes,and based on this,a multi-rotor drone flight mode based on deep learning is proposed.With the identification method,the average identification accuracy rate reaches 94.5%.(3)The distance-Doppler feature extraction algorithm for multi-rotor UAV based on multi-frame accumulation detection and the micro-motion feature extraction method of multi-rotor UAV based on the flicker phenomenon are proposed,which realize the extraction of motion and structure features of multi-rotor UAVs.The motion feature extraction algorithm was verified by the measured data of external radiation source radar based on broadcast and television signals,and the frequency band line and micro-Doppler bandwidth of the UAV motion process were extracted.A flicker-based micro-motion feature extraction method for multi-rotor UAVs is proposed,which can effectively extract the characteristics of the number of rotors,blades,rotor speed and length of multi-rotor UAVs,and provide the basis for the further identification of multi-rotor UAV models.