基于激光成像雷达的未知目标相对位姿估计算法

doi:10.16182/j.issn1004731x.joss.201705023

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (5): 1103-1111.doi: 10.16182/j.issn1004731x.joss.201705023

基于激光成像雷达的未知目标相对位姿估计算法

宋亮¹, 李志¹, 马兴瑞²

1.中国空间技术研究院钱学森空间技术实验室,北京 100081;
2.广东省政府,广东广州 510031

收稿日期:2015-02-10 修回日期:2015-04-27 出版日期:2017-05-08 发布日期:2020-06-03
作者简介:宋亮(1986-),男,辽宁,博士生,研究方向为航天器制导、导航与控制;李志(1966-),男,辽宁,硕士,研究方向为航天器动力学与控制;马兴瑞(1959-),男,山东,博士,教授,研究方向为飞行器动力学。
基金资助:
国家自然科学基金(61403392)

LIDAR-Based Relative Position and Attitude Filtering for Unknown Targets

Song Liang¹, Li Zhi¹, Ma Xingrui²

1. China Academy of Space Technology, Qian Xuesen Laboratory of Space Technology, Beijing 100091, China;
2. Government of Guangdong Province, Guangzhou 510031, China

Received:2015-02-10 Revised:2015-04-27 Online:2017-05-08 Published:2020-06-03

摘要/Abstract

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。

关键词: 激光成像雷达, 相对位姿估计, 未知目标, 视觉相对导航, 扩展卡尔曼滤波

Abstract: A LIDAR-Based Extended Kalman Filter (EKF) for relative position and attitude estimation of unknowns target was proposed. The relative position and attitude between the target and a servicing spacecraft was solved by the Iterative Closet Point (ICP) using LIDAR point cloud data, which served as the EKF's measurement input. The system states of EKF include the relative attitude, angular velocity, inertia ratios, relative position, relative velocity, and the position/attitude of target measurement reference frame with respect to target principle frame. The proposed filter estimated the relative position and attitude as well as the unknown parameters of the target. To improve the confidence of numerical simulation, geomagic was used to simulate the point cloud data of LIDAR. A simulation based on Matlab verifies the proposed algorithm.

Key words: LIDAR, relative position and attitude estimation, unknown object, vision-based relative navigation, extended Kalman filter

中图分类号:

TP391.9

宋亮, 李志, 马兴瑞. 基于激光成像雷达的未知目标相对位姿估计算法[J]. 系统仿真学报, 2017, 29(5): 1103-1111.

Song Liang, Li Zhi, Ma Xingrui. LIDAR-Based Relative Position and Attitude Filtering for Unknown Targets[J]. Journal of System Simulation, 2017, 29(5): 1103-1111.

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基于激光成像雷达的未知目标相对位姿估计算法

LIDAR-Based Relative Position and Attitude Filtering for Unknown Targets

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