CubeSat-Based Lunar Map Refinement Utilizing Surface Beacons and a Monocular Camera

Tyler J. Gardner, M. Hansen, Natalie Wisniewski, Randall S. Christensen
{"title":"CubeSat-Based Lunar Map Refinement Utilizing Surface Beacons and a Monocular Camera","authors":"Tyler J. Gardner, M. Hansen, Natalie Wisniewski, Randall S. Christensen","doi":"10.1109/PLANS46316.2020.9109980","DOIUrl":null,"url":null,"abstract":"SpaceX, Blue Origin, NASA, and others have recently proposed autonomous missions in preparation for new manned missions to the moon. Traditional approaches based solely on inertial navigation are not accurate enough to autonomously land a vehicle on hazardous lunar terrain, therefore Terrain Relative Navigation is being explored to supplement inertial navigation. Terrain Relative Navigation (TRN) is a capability that uses images of local terrain captured with a camera and/or imaging LIDAR to estimate the position and/or velocity of a spacecraft. Many TRN methods estimate the craft's absolute position by comparing sensor imagery to a crater/landmark database, global map, or another similar reference set. Because of the limited availability of high resolution lunar maps, the global accuracy of lunar TRN is currently limited to approximately 100 m. One compelling solution to improving global map resolution is to utilize an array of low cost CubeSats to image the lunar surface and refine existing maps. This paper explores the effectiveness of such a mission. In particular, the objective of this analysis is to determine the sensitivity of mapping uncertainty to sensor errors.","PeriodicalId":273568,"journal":{"name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PLANS46316.2020.9109980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

SpaceX, Blue Origin, NASA, and others have recently proposed autonomous missions in preparation for new manned missions to the moon. Traditional approaches based solely on inertial navigation are not accurate enough to autonomously land a vehicle on hazardous lunar terrain, therefore Terrain Relative Navigation is being explored to supplement inertial navigation. Terrain Relative Navigation (TRN) is a capability that uses images of local terrain captured with a camera and/or imaging LIDAR to estimate the position and/or velocity of a spacecraft. Many TRN methods estimate the craft's absolute position by comparing sensor imagery to a crater/landmark database, global map, or another similar reference set. Because of the limited availability of high resolution lunar maps, the global accuracy of lunar TRN is currently limited to approximately 100 m. One compelling solution to improving global map resolution is to utilize an array of low cost CubeSats to image the lunar surface and refine existing maps. This paper explores the effectiveness of such a mission. In particular, the objective of this analysis is to determine the sensitivity of mapping uncertainty to sensor errors.
利用表面信标和单目相机的基于立方体卫星的月球地图精化
SpaceX、蓝色起源(Blue Origin)、美国国家航空航天局(NASA)和其他公司最近都提出了自主任务,为新的载人登月任务做准备。传统的基于惯性导航的方法在月球危险地形上的自动着陆精度不高,因此,地形相对导航正在探索作为惯性导航的补充。地形相对导航(TRN)是一种利用相机和/或成像激光雷达捕获的局部地形图像来估计航天器位置和/或速度的能力。许多TRN方法通过将传感器图像与陨石坑/地标数据库、全球地图或其他类似参考集进行比较来估计航天器的绝对位置。由于高分辨率月球地图的可用性有限,目前月球TRN的全球精度限制在100米左右。提高全球地图分辨率的一个引人注目的解决方案是利用一组低成本的立方体卫星对月球表面进行成像,并改进现有的地图。本文探讨了这一使命的有效性。特别是,本分析的目的是确定映射不确定性对传感器误差的敏感性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信