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作 者:陈斌[1] 郗厚印 张晓东[2] 罗敏[2] 郭治栋 CHEN Bin;XI Houyin;ZHANG Xiaodong;LUO Min;GUO Zhidong(College of Artificial Intelligence,Beijing University of Posts and Telecommunications,Beijing 100876,China;Beijing Institute of Spacecraft System Engineering,Beijing 100094,China)
机构地区:[1]北京邮电大学人工智能学院,北京100876 [2]北京空间飞行器总体设计部,北京100094
出 处:《航空学报》2023年第1期239-250,共12页Acta Aeronautica et Astronautica Sinica
基 金:国家自然科学基金(62073033)。
摘 要:针对局部结构相似及翻滚遮挡下目标动态特性辨识问题,提出一种融合疏密度指标与全局测地线距离的空间非合作目标点云配准方法。首先,引入球面投影法,将不规则的空间目标点云映射到规则的球面流形上。然后,设计基于点云离散程度的疏密度评价指标,将球面点云划分为不同的局部点云子集,在此基础上构建全局测地线距离矩阵以增强点云局部形状信息的感知能力。最后,依据全局测地线距离矩阵推导建立了场景点云与模型点云间配准矩阵,实现空间非合作目标的动态特性辨识。仿真与试验结果表明:提出的算法在目标局部结构相似及点云缺失下的配准精度优于最近迭代点(ICP)算法与基于凸包粗配准的改进ICP算法。To realize identification of the dynamic characteristics of the space targets with local structural similarity and tumbling occlusion,a novel point cloud registration method is proposed for the space non-cooperative target by using the density index and global geodesic distance.First,the spherical projection method is introduced to map the irregular point cloud of the space target to the regular spherical manifold.Then,a density evaluation index based on the dispersion degree of point cloud is designed to divide the spherical point cloud into local subsets.On this basis,a global geodesic distance matrix is constructed to enhance the perception of the information of the local shape of the point cloud.Finally,according to the global geodesic distance matrix,a registration matrix between the scene point cloud and the model point cloud is established to realize the dynamic characteristic identification of the space non-cooperative target.Simulation and experimental results show that with similar target local structures and missing point clouds,the proposed algorithm has better registration accuracy compared to Iterative Closet Point(ICP)algorithms and improved ICP algorithms based on convex hull coarse registration.
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