Research On UAV Image Transmission Signal Analysis And Recognition

In recent years,the UAV industry has grown rapidly.At the same time,its widespread use has also brought issues such as privacy and security,and brought huge safety risks to aviation activities and key locations.This has prompted the research of UAV detection technology.Compared with active detection technology,passive detection technology has the advantages of low cost and low complexity.The analysis and identification of UAV image transmission signals is the premise and important link of UAV passive detection,and has great significance and value to in the anti-UAV field.At present,the privatization of UAV manufacturers’image transmission technology has brought many difficulties and challenges to the analysis and identification of image transmission signals.The main innovation of this thesis is the blind analysis of UAV image transmission signals and the research on the identification of synchronization sequences.The main contents are as follows:1.After explaining the UAV technology background,this thesis builds a signal acquisition platform based on Software Defined Radio(SDR).As for UAV image transmission technology,this thesis introduces three self-developed technologies of DJI:Lightbridge,Ocusync and Ocusync2.0 through investigation and comparison.As for the UAV signal acquisition platform,this thesis uses USRP B210 and GNU Radio to build this platform,and details the hardware structure,implements a universal signal acquisition software,determines the center frequency and other parameters through actual measurement,explains the differences in the signal acquisition process of the three UAVs.2.This thesis improves the traditional OFDM(Orthogonal Frequency Division Multiplexing)signal preprocessing technology route to carry out UAV image transmission signal preprocessing.For the blind estimation of image transmission signal parameters,on the basis of OFDM time parameter estimation algorithm based on cyclic autocorrelation,a parameter estimation algorithm based on the characteristics of time parameters is proposed to accurately estimate the source sampling rate,cyclic prefix(CP)length and symbol length of the measured image transmission signals.The improved preprocessing does not need to accurately estimate bandwidth and signal-to-noise ratio(SNR),but only needs a rough bandwidth estimate;and can accurately estimate the source sampling rate,so it does not require interpolation and re-acquisition,thereby reducing the processing complexity.For time-frequency calibration,after analyzing the effects of timing offset and frequency offset on constellation,the maximum likelihood synchronization based on CP and frequency offset correction algorithm are used to time-frequency calibration.3.A complete and detailed blind analysis of UAV image transmission signals is performed without any prior information for the first time in this thesis.Blind analysis mainly uses the auto-correlation and cross-correlation characteristics of the signals,and draws on some features of classic OFDM systems.For the first time,two UAV image transmission signals were analyzed in detail from five aspects:frame structure,synchronization signal,pilot signal,subcarrier allocation and modulation.This thesis also summarizes the analysis results of UAV image transmission signals,and compares and analyzes the design concepts of DJI’s Lightbridge and Ocusync image transmission technologies in terms of CP length,pilot pattern,subcarrier allocation and theoretical transmission rate.4.In this thesis,the sequence recognition of UAV image transmission signals’synchronization sequences is performed for the first time,and the generation formula of two UAV synchronization sequences is cracked.For Phantom 4 Advanced’s synchronization signal,this thesis obtains its sequence samples and analyzes its time-frequency characteristics.For Phantom 4 Pro V2.0 and Mavic 2,this thesis verifies that the synchronization sequence and pilot sequence of these two UAVs are ZC(Zadoff-Chu)sequences,and analyzes the sequence generation formula for the first time.At the end of this thesis,the root indices of the synchronization sequence and the pilot sequence under different bandwidths of the two UAVs are also tested.These results are of great significance for the subsequent research on passive positioning technology.