Research On Detection And Tracking Technology Of Rotary Wing UAV Based On Lidar

Although Unmanned Aerial Vehicle(UAV)have a wide range of applications due to their low cost,high safety,and strong maneuverability,they will pose potential safety threats to the external environment and personnel.Therefore,it is necessary to carry out research on UAV target detection and tracking methods to provide technical support for effective UAV flight monitoring to avoid personal injury and material damage.The target detection methods of UAV are mainly divided into two types,including machine vision and lidar according to the different detection equipment.Among them,the method of machine vision is to use vision sensors such as cameras to achieve target detection with the help of methods and technology research in the field of computer vision.Due to the low cost and easy industrialization of vision sensors,machine vision methods are widely used in fields such as video surveillance and unmanned driving.However,it is difficult for the machine vision method to detect the depth information of the target,which affects its practical application effect for the detection and tracking of the UAV..Compared with the method of machine vision,the use of lidar as a sensor can detect the depth information of the target,so this article adopts the method based on lidar to realize the detection and tracking of UAV.The specific research content of this thesis is as follows.Firstly,the widely used rotary-wing UAV is taken as the research object.An overall framework based on lidar for target detection and tracking is proposed.In terms of hardware design,after in-depth analysis of the characteristics of typical products at home and abroad,a hybrid solid-state lidar suitable for this article was determined.At the same time,combined with the current multi-type embedded processor characteristics and data processing requirements,the heterogeneous system on chip Zynq is selected to realize the data acquisition and processing.In terms of software schemes,the cross-compilation scheme required by the data acquisition program is designed,and a clustering detection algorithm suitable for point cloud data and a tracking algorithm scheme based on particle filtering is proposed.Then,Based on the software algorithm scheme,a target detection algorithm based on Euclidean distance clustering and a target tracking algorithm based on particle filter are proposed.The sparseness of the UAV point cloud data samples makes it impossible to apply machine learning methods for target detection.Therefore,this thesis uses an algorithm based on Euclidean distance clustering to detect the target,by setting the maximum number of point clouds allowed in a category in the cluster.And the minimum number of point clouds and the tolerance threshold between two adjacent points realize the detection of UAV.On this basis,the particle filter algorithm can solve the advantages of non-linear and non-Gaussian problems,construct the state transition equation of the UAV,and establish the observation equation of the lidar at the same time,and realize the tracking of the UAV by establishing the particle filter model.Using methods based on clustering and particle filtering,the detection and tracking of UAVs are completed.Finally,comprehensive experiment evaluations of UAV detection and tracking are implemented.The data acquisition unit of LiDAR is constructed by using the heterogeneous system on chip.It mainly completes the transplantation of Linux operating system to build an operating environment that can run algorithms.In the operating system environment,cross-compilation tools are used to generate executable programs that can run on the heterogeneous system on chip on the host computer,so as to realize crosscompilation of data acquisition programs.In order to verify the effectiveness of the algorithm and the realization of hardware functions,three groups of verification experiments were designed and completed,in which the detection accuracy experiment verified the accuracy of the clustering based target detection algorithm,the detection range experiment showed that the LiDAR could detect the range of the UAV,and the UAV dynamic flight experiment verified that the particle filter algorithm could track the UAV,and at the same time verified the successful transplantation of Linux operating system and the correct operation of the data acquisition program.