Research On Unmanned Aerial Vehicle (UAV) Detection And Implementation Based On External Radiation Source

While UAVs are widely penetrating into various fields,the incidents of UAV "black flight" are also intensifying,which seriously infringe on the interests of the state,society and individuals.In order to effectively detect UAV targets,this thesis explores UAV detection and implementation techniques from the perspective of multi-frequency external radiation source radar,and the research content and achievements are as follows:(1)A multi-frequency external radiation source selection method based on fuzzy evaluation and consistent ranking method is proposed.Firstly,the detection performance of external radiation source radar is improved from the engineering reality to optimize the selection of multiple external radiation sources and analyze the performance indexes of external radiation source radar.Secondly,we solve the affiliation degree of selected indicators according to the affiliation degree function of fuzzy evaluation,and get the affiliation degree results of different detection sites A and B.Thirdly,the selection weights of A and B are derived according to the consistency ranking and entropy value method.Finally,according to the subordination of selection index and selection weight value to find out the comprehensive selection degree of multiple external radiation source signals of different detection sites of A and B,and simulation gives the selection difference of external radiation source signals under different subjective selection.The results show that the method can achieve the selection of multi-frequency external radiation source signals,providing a theoretical basis for subsequent multi-frequency detection methods.(2)A multi-frequency external radiation source UAV detection method based on HOG+SVM is proposed.Firstly,the UAV external radiation source echo signals in DTMB,FDD LTE and FM bands are received in time,and their cyclic spectrum contour maps are calculated separately using the FFT accumulation algorithm(FAM),and then the Histogram of oriented gradients(HOG)features of each cyclic spectrum contour map are extracted.Finally,the HOG features are fed into the Support vector machine(SVM)classifier for detection and identification.The actual measurement results show that the detection performance and stability are better using multi-frequency detection compared with single-frequency detection,and the detection rate reaches 82% at a signal-to-noise ratio of 5 d B,which is 5-7 d B better than that of single-frequency detection.(3)An external radiation source radar detection system based on ZYNQ+AD9361 is designed and implemented.Firstly,the external radiation source signal acquisition subsystem is designed,and the ZYNQ master control module,AD9361 engineering construction,initialization of AD9361 and gigabit network transmission module are analyzed in detail.Secondly,the human-computer interaction is carried out by designing the upper computer,and the feasibility of hardware system reception is verified and analyzed.Thirdly,from the micro-motion characteristics of UAVs,the degree of influence of the UAV rotor with or without metal tinfoil film coverage and the different rotor length on the micro-Doppler effect of the UAV rotor scattering signal in outdoor environment was investigated for different types of UAVs.Finally,the hardware system designed in this paper is tested and experimented,and the results show that the system can realize the reception of multi-frequency external radiation source signals,which can realize the fast and accurate detection of UAV targets.