Study on Terrain Matching Method Based on Cater Detection

  • Yiming Ke
  • , Yong Zhang*
  • , Hanchen Liu
  • , Shisong Li
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Chang'e-4 lunar probe carrying the Moon Rabbit 2 lunar rover was lifted off by the Long March 3B launch vehicle and landed on the back side of the Moon after 26 days of space flight, becoming the world's first probe to land on the back side of the Moon. In this paper, a terrain matching method based on crater detection is designed using the images taken by Chang'e-4 on the back side of the Moon. This method firstly establishes a local land marker library based on the existing data and the intended landing area of the spacecraft, then identifies and labels the craters in the images taken by the landing camera, and finally matches the craters in the captured images with the data in the land marker library to obtain the position information of the spacecraft during the landing process.

Original languageEnglish
Title of host publicationProceedings of 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021
EditorsBing Xu, Kefen Mou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages506-514
Number of pages9
ISBN (Electronic)9781665428767
DOIs
StatePublished - 2021
Event2nd IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021 - Chongqing, China
Duration: 17 Dec 202119 Dec 2021

Publication series

NameProceedings of 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021

Conference

Conference2nd IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021
Country/TerritoryChina
CityChongqing
Period17/12/2119/12/21

Keywords

  • feature matching
  • image localization
  • land mark library
  • semantic segmentation
  • target detection

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