Non-cooperative target pose estimation based on improved iterative closest point algorithm
基于改进迭代最近点算法的非合作目标位姿评估
改良された反復最接近点アルゴリズムに基づく非協調的ターゲットポーズ推定
개선된 반복 근접점 알고리즘을 기반으로 하는 비협조적 대상 포즈 추정
Estimación de la pose del objetivo no cooperativa basada en un algoritmo de punto más cercano iterativo mejorado
Estimation de pose cible non coopérative basée sur un algorithme de point le plus proche itératif amélioré
Некооперативная оценка положения цели на основе улучшенного итеративного алгоритма ближайшей точки
Zijian ZHU 朱子健 ¹, Wenhao XIANG 向文豪 ³, Ju HUO 霍炬 ¹ ², Ming YANG 杨明 ¹, Guiyang ZHANG 张贵阳 ¹, Liang WEI 魏亮 ¹
¹ Department of Astronautics, Harbin Institute of Technology, Harbin 150006, China
中国 哈尔滨 哈尔滨工业大学航天学院
² Department of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150006, China
中国 哈尔滨 哈尔滨工业大学电气工程及自动化学院
³ Systems Engineering Research Institute, China State Shipbuilding Corporation Limited, Beijing 100036, China
中国船舶工业集团有限公司 系统工程研究院
Journal of Systems Engineering and Electronics, 22 February 2022
Abstract
For localisation of unknown non-cooperative targets in space, the existence of interference points causes inaccuracy of pose estimation while utilizing point cloud registration. To address this issue, this paper proposes a new iterative closest point (ICP) algorithm combined with distributed weights to intensify the dependability and robustness of the non-cooperative target localisation.
As interference points in space have not yet been extensively studied, we classify them into two broad categories, far interference points and near interference points. For the former, the statistical outlier elimination algorithm is employed. For the latter, the Gaussian distributed weights, simultaneously valuing with the variation of the Euclidean distance from each point to the centroid, are commingled to the traditional ICP algorithm.
In each iteration, the weight matrix W in connection with the overall localisation is obtained, and the singular value decomposition is adopted to accomplish high-precision estimation of the target pose. Finally, the experiments are implemented by shooting the satellite model and setting the position of interference points.
The outcomes suggest that the proposed algorithm can effectively suppress interference points and enhance the accuracy of non-cooperative target pose estimation. When the interference point number reaches about 700, the average error of angle is superior to 0.88°.
