@inproceedings{55f7ad1340554cf5ac02eae94ffec10e,
title = "Aircraft Autonomous Positioning Based on a Coarse to Fine Multi-modal Image Registration Scheme",
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\%.",
keywords = "autonomous position, coarse-to-fine image matching, RANSAC",
author = "Fangde Sun and Wenxing Fu and Xiaohui Lu and Jing Dong and Songlai Han",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021 ; Conference date: 22-01-2021 Through 24-01-2021",
year = "2021",
month = jan,
day = "22",
doi = "10.1109/ICPECA51329.2021.9362610",
language = "英语",
series = "Proceedings of 2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "934--939",
booktitle = "Proceedings of 2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021",
}