영상 기반 항법을 위한 가우시안 혼합 모델 기반 파티클 필터 Particle Filters using Gaussian Mixture Models for Vision-Based Navigation

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Vision-based navigation of unmaned aerial vehicle is a significant technology that can reinforce the vulnerability of the widely used GPS/INS integrated navigation system. However, the existing image matching algorithms are not suitable for matching the aerial image with the database. For the reason, this paper proposes particle filters using Gaussian mixture models to deal with matching between aerial image and database for vision-based navigation. The particle filters estimate the position of the aircraft by comparing the correspondences of aerial image and database under the assumption of Gaussian mixture model. Finally, Monte Carlo simulation is presented to demonstrate performance of the proposed method.
Publisher
KOREAN SOC AERONAUTICAL & SPACE SCIENCES
Issue Date
2019-11
Language
Korean
Article Type
Article
Citation

JOURNAL OF THE KOREAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, v.47, no.4, pp.274 - 282

ISSN
1225-1348
DOI
10.5139/JKSAS.2019.47.4.274
URI
http://hdl.handle.net/10203/268193
Appears in Collection
AE-Journal Papers(저널논문)
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