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The Research On Direction Finding Intersection And Tracking Technology

Posted on:2020-10-08Degree:MasterType:Thesis
Country:ChinaCandidate:R MaFull Text:PDF
GTID:2392330599459643Subject:Electromagnetic field and microwave technology
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In recent years,with the rapid development of the drone industry,the scope of application of drones has become wider and wider.Correspondingly,the control of drones has also been urgently needed.The distributed passive positioning system is based on the receiving signals of multiple monitoring terminals,which can realize the functions of unmanned aerial vehicle signal positioning and tracking trajectory.Passive positioning system enables passive detection and location acquisition of typical targets such as drones to meet major event radio security requirements.This paper mainly studies and optimizes the distributed passive positioning system from the key technologies of direction-finding intersection and tracking trajectory,including:1.The principle of direction finding intersection is analyzed and discussed.Firstly,the direction finding intersection algorithm in 2D plane and 3D space is introduced.Through the principle derivation of the direction finding intersection location algorithm,the influence of positioning accuracy of direction finding intersection location is analyzed.Factors,combined with GDOP for detailed simulation of various influencing factors.Then,from the improvement of positioning accuracy,the positioning performance in the region is evaluated by observing the GDOP simulation map under ideal conditions.In the non-ideal situation,an optimal mathematical model is established to obtain the objective geometric dilution in the region as the objective function.The particle swarm optimization algorithm is used to solve the model,and the optimal site distribution is selected in the two-dimensional plane region.Simulation analysis also verifies the effectiveness of the algorithm.2.Specifically,the multi-station intersection location in the two-dimensional plane is analyzed.Considering the direction-finding error of the monitoring station and the multi-target direction-finding convergence problem in the geometric positioning process,two optimization points are proposed in this paper: The first is that in the process of multi-station intersection positioning,due to the direction finding error,the direction lines of multiple monitoring stations will not meet the real position of the target signal source.For this phenomenon,the intersection location model based on least squares optimization is proposed.The second is that when multi-target positioning is carried out in multiple monitoring stations,a large number of false result points may be generated.For this phenomenon,the data sorting method when the direction-finding angle corresponds to the signal source relationship is proposed,and the orientation is given.False point culling when the relationship between the angle and the signal source is not clear.At the same time,the estimation error caused by the direction error and multi-target positioning of the monitoring station is optimized,the generation of false positioning points is reduced,and the performance of the target positioning system is improved.3.The problem of tracking and localization of signal source targets is studied.The Kalman filter technique is expounded.The extended Kalman filter(EKF)and unscented Kalman filter(UKF)are mainly discussed.In addition,considering the fact that the target motion model is not single,The IMMUKF algorithm based on multiple models is introduced.According to different filtering and tracking methods,based on the direction-finding intersection location,the performance of EKF and UKF in maneuvering target tracking is compared and simulated.The superiority of IMM algorithm in multi-model is verified,and the tracking data is tested by test data.The effect was verified.
Keywords/Search Tags:Direction finding intersection positioning, Tracking technique, GDOP, Kalman filtering
PDF Full Text Request
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