Research And Implementation Of Anti-UAV System Based On Electromagnetic Technology

In the past two years,the civil small unmanned aerial vehicle(UAV)market has developed rapidly.Beginning in 2013,professional small civil UAV manufacturers such as DJI and Parrot gradually entered the field of vision of consumers at home and abroad,and "aerial photography" gradually became popular.However,because the market is still in the early stage of development,the management methods for small civil aircraft are not perfect in policy,and most consumers do not have the opportunity to receive professional training for pilots,coupled with the unfamiliar flying regulations for small UAVs,this has caused the phenomenon of "black flight" of small civil UAVs.Therefore,research and development of electromagnetic counter-production technology for small drones is an urgent task.In this thesis,after analyzing the research status of anti-UAV technology at home and abroad,aiming at the current frequency band and signal characteristics of UAV,on the basis of summarizing the previous work,the identification and jamming methods of UAV are studied in depth.The main work includes:(1)The communication system of the current civil small UAV is studied.Firstly,WiFi communication system and frequency hopping communication system which are widely used in UAV are deeply studied,and then the principle of common communication jamming methods is studied.It provides a theoretical basis for the later LSTM-based UAV signal recognition algorithm and the corresponding interference method.(2)A small UAV signal recognition and interference platform is designed.Firstly,based on PC and USRP X310 software radio platform,the UAV signal acquisition and processing platform is built;then,based on raspberry pie and wireless network card,the WiFi signal jamming platform is built;finally,the hardware design of the signal jamming platform based on MCU+VCO scheme is given.(3)The algorithm and software design in the signal recognition and interference platform of the small drone is completed.Firstly,the neural network based UAV signal recognition algorithm is proposed.The methods of signal acquisition and feature extraction are given.The theoretical analysis and design of the neural network model based on LSTM are given.The training process of the network is given.The training results are presented.Then the interference methods for the UAVs using WiFi communication are proposed,including the verification verification attack and the flood verification attack,and the corresponding implementation is implemented.Finally,the software design in the signal blocking interference platform is given.After testing,the UAV counter system designed in this thesis can effectively complete the identification and interference work of the UAV.The final result is that when the drone enters the monitoring area,the system can intercept the drone signal and identify its model,and take targeted interference measures for different types of drones.