摘要
2021年5月15日,中国“祝融号”火星车成功登陆火星乌托邦平原南部,首次独立在一次任务中成功实现“绕、落、巡”的探测目标。火星车高精度定位对于火星任务的顺利实施和后续科学研究都至关重要,如火星车路径规划和规避危险区域。详细介绍了基于多源影像的“祝融号”火星车定位方法,采用由粗至精的策略实现了着陆点在轨道器高分影像的精确定位,采用相对定位和绝对定位相结合的地面修正方式实现了火星车站点的连续高精度定位。对多源影像的定位方法进行了实验验证,结果表明基于视觉的着陆点定位精度能优于高分轨道器影像1个像素,基于光束法平差的相对定位精度在距离10 m左右时优于3%。基于多源影像的定位方法已成功应用于“祝融号”火星车定位,高精度的定位结果有力地保障了火星车在火面进行安全高效移动。
Zhurong rover landed on the southern part of Utopia Planitia of Mars on 15 May,2021(UTC+8),marking that China successfully fulfilled the goals of“orbiting,landing on and roving around”Mars on its own for the first time.Localization of the rover is critical for supporting science and engineering operations in planetary rover missions,such as rover traverse planning and hazard avoidance.This paper introduced the localization method of Zhurong rover based on multi-source images in detail.Based on the coarse-to-fine strategy,the accurate landing positioning was achieved in the Digital Orthophoto Map(DOM)generated by the high resolution orbiter-image.Using the ground correction method combining relative localization and absolute localization,highprecision continuous localization of the rover was realized.Simulation experiment shows that the localization accuracy of the lander was within a pixel of the DOM generated by the high resolution orbiter-image,and the relative localization accuracy based on the Bundle Adjustment(BA)was better than 3%when the distance was about 10 meters.The methods have been successfully applied to the localization of Zhurong rover.The high-precision localization results greatly support the rover’s efficiently roving on Mars surface and avoiding potentially dangerous regions.
作者
王镓
李达飞
何锡明
成子青
许倩
钱雪茹
万文辉
WANG Jia;LI Dafei;HE Ximing;CHENG Ziqing;XU Qian;QIAN Xueru;WAN Wenhui(Beijing Aerospace Control Center,Beijing 100094,China;Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China)
出处
《深空探测学报(中英文)》
CSCD
北大核心
2022年第1期62-71,共10页
Journal Of Deep Space Exploration
基金
国家自然科学基金(41771488,11773004)。
关键词
祝融号
多源影像
着陆点定位
站点定位
航迹推算
Zhurong
multi-source image
landing localization
site localization
Dead-Reckoning