基于激光成像雷达的未知目标相对位姿估计算法

发布时间：2018-06-23 09:02

本文选题：激光成像雷达 + 相对位姿估计　；参考：《系统仿真学报》2017年05期

【摘要】：为解决对空间未知目标的相对位置、姿态估计问题,以激光成像雷达作为测量敏感器,提出了基于扩展Kalman滤波(EKF,Extended Kalman Filter)的相对位姿估计算法。采用迭代最近点算法(Iterative Closest Point,ICP)对激光雷达的点云测量数据进行解算,得到相对位姿粗值并将其作为位姿估计算法的测量输入。以相对姿态、角速度、惯量比、相对位置、相对速度和目标测量参考系的位姿作为滤波状态,算法在对相对位置和姿态估计的同时,可辨识出目标的未知参数。为提高数值仿真的可信度,用Geomagic软件模拟点云测量。采用Matlab进行数值仿真,验证了新算法的有效性。
[Abstract]:In order to solve the problem of relative position and attitude estimation of unknown targets in space, a relative attitude estimation algorithm based on extended Kalman filter (EKF) is proposed using laser imaging radar as measurement sensor. The iterative closest Point Point (ICP) algorithm is used to calculate the point cloud measurement data of lidar, and the coarse relative position is obtained and used as the measurement input of the position and attitude estimation algorithm. Using relative attitude, angular velocity, inertia ratio, relative position, relative velocity and position of reference frame of target measurement as filtering states, the unknown parameters of the target can be identified by the algorithm while estimating the relative position and attitude. In order to improve the reliability of numerical simulation, point cloud measurement is simulated with Geomagic software. The validity of the new algorithm is verified by numerical simulation with Matlab.
【作者单位】：中国空间技术研究院钱学森空间技术实验室;广东省政府;
【基金】：国家自然科学基金(61403392)
【分类号】：TN958.98

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