A Linear Array Lidar Imaging Mechanism And Three-dimensional Reconstruction For Space Non-cooperate Instability Targets

The 3D(three-dimensional)reconstruction of space instability and non-cooperative targets can provide more accurate guidance for the service spacecraft approaching the out-of-control spacecraft.This technology is of great significance in extending the service life of spacecraft and improving the efficiency of space orbit resource use.The non-cooperative goal of space instability is a malfunction or abandoned satellite under the action of space perturbation.Its motion characteristics are uncertain,and it is a priori information is missing.It has non-cooperative characteristics and cannot communicate through inter-satellite links.In the space measurement load,the linear array laser imaging radar has the advantages of strong anti-jamming capability and little influence of illumination,and the urgent need for non-cooperative target measurement applications in space instability.The linear array laser imaging radar has become an ideal measurement tool for 3D reconstruction of space targets.Aiming at the problem of three-dimensional reconstruction of spatially unstable non-cooperative targets.Using linear array lidar measurement methods,theoretical analysis and simulation verification are performed from the aspects of linear array radar imaging mechanism analysis and simulation,point cloud distortion recovery,target 3D reconstruction,and reconstruction quality evaluation methods.The main work of this article is as follows:(1)The space instability and non-cooperative target working condition environment are established,including target movement mechanism and radar scanning mechanism;According to the parameters such as lidar resolution and noise,the target point cloud data is generated,the point cloud coordinate system is converted,the corresponding target point cloud is generated at different times,the target visible point discrimination from the radar perspective is performed.The measurable point cloud extraction mechanism of double slice method is proposed,and the imaging point cloud data is output.(2)Achieving the point cloud distortion recovery requires solving the target spin and nutation motion parameters.The iterative closest point ICP registration algorithm is used to solve the transformation relationship of the point cloud of adjacent frames.The movement increment within the target difference time is solved.3D reconstruction of the overall shape of the target based on the registration results.The reconstruction result evaluation system was established,and the reconstruction quality was evaluated from the aspects of reconstruction point cloud accuracy and average density.(3)Through MATLAB and Visual Studio software for simulation experiment verification analysis.The target CAD modeling,point cloud data conversion,lidar imaging scanning and result output are performed according to the established linear array lidar imaging mechanism flow.According to the distortion correction model,point cloud registration method,reconstruction scheme and reconstruction quality assessment method,the whole process of the target 3D shape restoration is simulated.The feasibility and accuracy of the reconstruction plan are verified.Furthermore,the redundancy of the scanned data is analyzed,and an efficient and high-precision point cloud data screening method is proposed.Finally,through the GUI module of MATLAB,the point cloud extraction algorithm of the dynamic target line scan measurable part in the system model is integrated.(4)The experimental results show that the data extraction of the measurable parts of the space target is reasonable and accurate,and the data output frequency is 1Hz.The reconstruction results meet the task index requirements.The average density of the reconstructed point cloud is 19 mm.The accuracy of the reconstructed point cloud is 90 mm.The research provides data support and reference for ground verification and on-orbit applications.