Signal Analysis And Feature Extraction For UAV Detection And Localization

With the rapid development of unmanned aerial vehicles(UAVs)technology,consumer grade UAV have low cost and simple operation,which has brought great convenience to the society.However,there are also many safety concerns,such as injury to personal and structure damage to building caused by the "black flight" of UAV.Therefore,drone detection and positioning technology is currently one of the research hotspots in this field.Existing UAV detection and positioning technologies are mainly based on sound,photo-electricity,radar and vision.These technologies have low accuracy in some special environments.However,the method of detecting and positioning UAVs through UAV signals is more tolerant to the environment.The advantages of Software-Defined Radio(SDR)are relatively low cost and has a flexible design.The SDR able to perform feature extraction and analysis on UAV signals.Hence,this thesis applies the UAV signal to perform feature extraction and analysis to detect and locate the UAV,and utilizes the SDR platform to test and verify this system.The research content of this thesis is as follows:Firstly,on the basis of detailed analysis of UAV signals,Empirical Mode Decomposition(EMD),Wavelet Transform(WT)and Short-Time Fourier Transform(STFT)are employed.These methods extract UAV vibration characteristics,movement characteristics and information entropy characteristics.The UAV signal detection algorithm is designed by using the machine learning classification algorithm and the features mentioned above.The UAV data is received in the real environment,and the UAV detection accuracy is tested and verified through the SDR platform.Subsequently,on the basis of introducing the channel model in detail,the Angle of Azimuth(AOA),Angle of Elevation(AOE)and Time of Flight(TOF)are estimated by the super-resolution parameter estimation algorithm.After analyzing the influence of the number of receivers on the positioning accuracy,a UAV positioning model based on multiple receivers is designed.The small-scale UAV positioning test verification is carried out through the SDR platform,and the large-scale positioning test verification is carried out through the Wireless Insite simulation software.In conclusion,the experiment results show that the UAV detection and positioning system designed in this thesis applying signal features achieves 95.57% detection accuracy,and the 3D spatial localization accuracy of 50% error is 1.16 meters in real environment.The 3D space positioning accuracy of 50% error is 2.35 meters in Wireless Insite simulation software.