Research On Distributed Passive Positioning Method For Unmanned Aerial Vehicles

UAVs are usually low-altitude and slow-flying targets,characterized by small size,low flying altitude,and slow speed,which makes it difficult for radar detection to identify and locate them.As UAV activity further increases,so do safety and privacy concerns.How to efficiently monitor and locate UAV has become a key issue.In passive positioning,the distributed observation stations do not need to send any signals to the UAV,but passively receive the signals sent by the UAV to complete the positioning.Passive positioning has the advantages of wide detection distance,low cost,and strong concealment.This thesis studies the distributed passive localization method for UAVs.The main research contents are as follows:(1)The signal of DJI PHATOM 4 ADVANCED UAV was collected and analyzed.The time domain and frequency domain characteristics of the signal are analyzed.It provides a theoretical basis for the observation station spectrum monitoring and signal feature identification.(2)Due to the problem of phase ambiguity in the single baseline phase interferometer,through the research on the long and short baseline phase interferometer,the simulation verifies that it can meet the angle measurement range and angle measurement accuracy at the same time.Due to the practical application of MUSIC algorithm,there is a problem that the coherent signal caused by multipath transmission or interference originates from the rank deficit of the correlation matrix.By smoothing the space of the MUSIC algorithm,the direction finding of the coherent signal source is realized.(3)Research on UAV passive direction finding cross-location technology.The performance of the pseudo-linear least squares method and the Gauss-Newton iterative algorithm is mainly analyzed and simulated,and the factors affecting the positioning accuracy are simulated and analyzed.On the basis of GDOP analysis and simulation of direction finding cross positioning,suggestions are given for UAV direction finding cross positioning: generally 3-4 observation stations are enough to meet the needs of direction finding cross positioning.Improving the accuracy of angle measurement can effectively improve the positioning accuracy.In three-station direction-finding positioning,the station layout method should generally choose triangular station layout.(4)The pseudolinear weighted least squares algorithm,Chan algorithm and Taylor algorithm in passive TODA location are analyzed and simulated.By analyzing the advantages and disadvantages of the three algorithms,a pseudolinear weighted least squares-Taylor algorithm is analyzed.Simulations have verified its feasibility and effectiveness: within the time error range of 1～22 ns,in a small range(2000 m)space,the positioning performance of the pseudolinear weighted least squares-Taylor algorithm is better than the above algorithms,close to CRLB.(5)The UAV passive positioning system is simulated by using Wireless InSite,and it is concluded that in a small range(2000 m)space,when the UAV is flying at a relatively high altitude(above 210 m),the TDOA method should be used.On the contrary,the direction finding cross positioning algorithm should be used,or the TDOA algorithm with direction finding parameters as auxiliary information.