全球定位系统2026，Vol.51Issue(2)：50-60,11.DOI:10.12265/j.gnss.2025244
地月空间DRO光学导航测角信息智能提取方法
DRO optical navigation:an intelligent and robust method for measurement extraction
赵玉涛 1左健宏 2舒磊正 1杨思亮3
作者信息
- 1. 中国科学院大学,北京 100049||中国科学院空间应用工程与技术中心,北京 100094
- 2. 中国科学院空间应用工程与技术中心,北京 100094||南京航空航天大学 航天学院,南京 211106
- 3. 深空探测实验室,北京 100195
- 折叠
摘要
Abstract
In distant retrograde orbit(DRO)optical autonomous navigation,traditional image-processing-based centroid extraction methods often suffer from severe performance degradation or even failure under extreme illumination and phase conditions,such as crescent and gibbous phases.These operating scenarios are characterized by significant target occlusion and non-uniform illumination,under which edge-based detection and fitting approaches become highly sensitive to noise and prone to convergence toward local optima,thereby constituting a major limitation for high-accuracy angle measurements.To address this challenge,this paper proposes a dual keypoint regression method based on deep geometric constraints,in which the conventional centroid extraction problem is reformulated as a feature learning task that jointly incorporates physical and geometric priors.The proposed method adopts YOLOv8-pose as the keypoint regression framework and introduces the physical centroid and the geometric center as jointly regressed targets.By exploiting the geometric constraints implied by the observable illuminated arc,the prediction space of the centroid in unobservable regions is effectively restricted,leading to enhanced robustness under extreme phase conditions.Validation experiments conducted on an on-orbit observation dataset generated by a high-fidelity virtual simulation engine demonstrate that,compared with the traditional ellipse-based direct method,the proposed approach reduces the angular measurement error decreases from 0.116° to 0.013°,corresponding to an order-of-magnitude improvement in angular accuracy.These results confirm the effectiveness and feasibility of the proposed method in complex deep-space imaging environments,providing a viable solution for high-reliability optical autonomous navigation.关键词
光学自主导航/质心提取/关键点回归/地月识别/在轨图像仿真Key words
optical autonomous navigation/centroid extraction/keypoint regression/Earth-Moon recognition/in-orbit image simulation分类
天文与地球科学引用本文复制引用
赵玉涛,左健宏,舒磊正,杨思亮..地月空间DRO光学导航测角信息智能提取方法[J].全球定位系统,2026,51(2):50-60,11.
