Aircraft Autonomous Positioning Based on a Coarse to Fine Multi-modal Image Registration Scheme

Fangde Sun, Wenxing Fu, Xiaohui Lu, Jing Dong, Songlai Han

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

1 Scopus citations

Abstract

In this paper, an autonomous positioning method based on coarse-to-fine multi-modal image matching is proposed for UAV navigation in GPS denied environment. Coarse image matching refers to roughly determining the approximate position of the real-time image in the reference image. Fine image matching refers to iterative matching around the position obtained by coarse image matching to achieve more accurate matching results. Besides, RANSAC is adopted to eliminate the outliers of image matching. After getting the result of image matching, we use PNP to estimate the position of the aircraft. The proposed position method has the advantages of high accuracy and reliability. The experimental results show that the average error of the position of the proposed method is 59%.

Original languageEnglish
Title of host publicationProceedings of 2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages934-939
Number of pages6
ISBN (Electronic)9781728190037
DOIs
StatePublished - 22 Jan 2021
Externally publishedYes
Event2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021 - Shenyang, China
Duration: 22 Jan 202124 Jan 2021

Publication series

NameProceedings of 2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021

Conference

Conference2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021
Country/TerritoryChina
CityShenyang
Period22/01/2124/01/21

Keywords

  • autonomous position
  • coarse-to-fine image matching
  • RANSAC

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