Research On Target Tracking And Position And Attitude Calculation Of Rotor UAV Based On Visual Navigation

With the continuous innovation of science and technology,unmanned aerial vehicle(UAV)have been widely used in various fields such as military and civilian.Autonomous landing of UAV is an important stage in the process of UAV flight.Because the classic GPS/INS integrated navigation system is difficult to provide accurate navigation information for the autonomous flight of UAV in various situations,the vision-based UAV landing technology has become one of the research focuses in the field of UAV control,and it also makes up for the vacancy of domestic UAV autonomous landing on mobile platform technology.In this paper,the four-rotor UAV is used as the experimental platform,and the sequence images taken by the airborne camera are taken as research objects.The techniques and methods such as computer vision,digital image processing and perspective projection are used to land in the autonomous landing stage of UAV.The problem of marker tracking,feature information extraction,and estimation of relative position and attitude parameters of UAV has been deeply studied.The problem oftarget tracking and pose calculation based on vision is mainly discussed.On the target tracking problem,the "H" shaped landing target image is designed,the SIFT feature information is extracted and matched,and the matching result is further improved by RANSAC algorithm.Based on the advantages of Camshift tracking algorithm and particle filtering,a particle filter tracking algorithm combining target color feature,SIFT feature and texture feature is proposed,and it’s work process is described in detail.Firstly,the initial position and size of the tracking window are determined according to the SIFT matching results.Then,the Camshift algorithm is used to optimize the particle propagation,and adjust the size and direction of the tracking window adaptively,and finally estimate the state of the tracking target.At the same time,three fusion strategies of feature information are proposed,and particle resampling technology is introduced to deal with particle degradation.Experiments verify that the tracking algorithm is effective and feasible in the case of target occlusion and similar color interference.On the problem of pose calculation,the image of the tracked area captured by the airborne camera is subjected to image processing such as threshold segmentation,median filtering and corner detection.The image of the feature point of the "H" shaped landing sign is obtained on the image.Then,based on the transformation relationship between the perspective projection model and the coordinate system,the UAV poseestimation model is established.Finally,the singular value decomposition method are used to solve the optimal solution of position and attitude information.In the experiment,the position and attitude information of UAV itself is compared with the experimental pose information,and the error is within the allowable range,which verifies the correctness of the algorithm.