Research On High-Precision Dynamic Target Positioning And Tracking Methods Of Unmanned Aerial Vehicle

For its advantages of good concealment, unafraid to casualties, simple operation, flexible use, long time of flight, and low cost, unmanned aerial vehicle(UAV) is widely used both in military fields and in civil aspects. In many applications of UAV, the tasks of dynamic target positioning and tracking are included, high or low accuracy of positioning and tracking directly determines the success or failure of the tasks. There is a great gap in UAV target tracking location fields between our country and developed countries, therefore, this paper carries out a research on high precision positioning and tracking methods for dynamic target of UAV. The main contents and the research results of the thesis are summarized as follows:(1) Single UAV target positioning method is studied. Using UAV photo-electric measuring system measures the relative azimuth Angle, pitching Angle, and distance of target, then target positioning and guidance equation is deduced by means of homogeneous coordinate transformation. This can calculate the target location information in the geodetic coordinate system(longitude L, latitude B, altitude H). And then the target is marked on the electronic map, in order to analyze and monitor the target.(2) Error analysis is carried out on the process of UAV target positioning, and the overall scheme of the high precision target positioning is proposed. This paper establishes target positioning error model first, uses the Matlab language to write UAV target simulation program, does a large number of simulation analysis of target location process based on the Monte Carlo. The relatively obvious factors that impact on the target location accuracy are found. On the basis, corresponding measures for increasing accuracy of target location are put forward, and then the high precision target positioning scheme based on UAV integrated navigation technology is proposed.(3) In view of the locating scheme which is proposed, this paper further studies of the UAV SINS/GPS integrated navigation technology. By using the Matlab/Simulink software to simulate SINS and GPS navigation systems, I verify the performance of systems, and analyze their advantages and limitations. Combine SINS with GPS by the optimal estimation algorithm Kalman Filter, complement each other, navigation and positioning accuracy is significantly higher than the precision of each system independently.(4) For the study of UAV target tracking state fusion estimation algorithm, this paper proposes an interactive multiple model particle filter algorithm based on CS model. Interactive multiple model particle filter algorithm can get a very good tracking effect only in choosing the right target motion model, the model parameters and model number. However, CS model adaptive filtering algorithm has high tracking precision, can truly reflect target mobility, but cannot automatically adjust. Therefore, combining these two kinds of algorithm, on the basis of the interactive multiple model particle filter algorithm, we can calculate the correction probability of model, adaptively adjust the most-positive, negative acceleration of the CS model, give full use of the advantages of two algorithms, eventually lead to increase tracking accuracy. The simulation verifies the effectiveness of the new algorithm, which is presented by the paper.