The Research On The Non-cooperative Detection And Decoding Technology For UAV Communication Signal

With the development of the drone market,various civilian Unmanned Aerial Vehicle(UAV)have been applied in public life.Meanwhile,civilian drones' application,raising many problems,is urged to be supervised.Passive location is an effective detective method by receiving the UAV signal to achieve target positioning.First of all,the key point is to detect UAV communication signal.As confidential material,the UAV communication system is not disclosed for public and there is little academic data in this field.This thesis focuses on the non-cooperative detection and decoding technology in UAV signal.The main contents are as follows:(1)Comprehensive analysis and research in typical civilian Micro-UAV signals.The preliminary step is to collect signal data including WiFi system,non-WiFi system,graphic transmission signal and remote-control signal.By analyzing those obtained data,characteristic parameters of various UAV signals in time-frequency domain are summarized.To study the core properties,OFDM signal mechanism,used in UAV communication system,is introduced and then unified to analyze the internal structures in UAV signal,which provides theoretical foundation of detection and identification technique in UAV signal.(2)The detection technique in non-cooperative UAV signal under low SNR condition.This section first establishes a hypothesis testing model on normalized delay autocorrelation method to deduce detection thresholds in Constant False Alarm Rate(CFAR)detection and theoretical probability.A multi-sets time-delay autocorrelation accumulation detection algorithm and a multi-pulse correlation matching filter detection algorithm are then derived based on the structural characteristics in WiFi and non-WiFi system.These algorithms are used to deduce detection threshold and then compared with the results obtained by Monte Carlo simulation in performance testing.Experimental results show that the mentioned algorithms can increase signal detection probability/accuracy in low SNR environment.(3)The decoding method of UAV equipped with WiFi system.For UAV with WiFi system,the UAV signals,adopt the IEEE 802.11a/g standard protocol,have the same signal form requiring a decoding method to distinguish its platform identification.Firstly,a physical layer coding process of IEEE 802.11a/g protocol is analyzed followed by a discussion of critical procedures in decoding process.On this basis,this section simulates the transmission,reception and decoding process of physical layer baseband signal and verifies its overall technological process and decoding performance.This method is validated by obtained UAV data.(4)Analysis of measured data of UAV under field tests.By conducting external experiments using existing detective devices,the detecting algorithms are verified respectively by those collecting and analyzing measured data.The results show that the mentioned algorithms can realize non-cooperative UAV signal detection in low SNR situations.