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Pose Estimation of Space Targets Based on Model Matching for Large-Aperture Ground-Based Telescopes

Zhengwei Li1,2, Jianli Wang1,*, Tao Chen1, Bin Wang1, Yuanhao Wu1
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, 13033, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
*Corresponding Author: Jianli Wang. Email: .

Computer Modeling in Engineering & Sciences 2018, 117(2), 271-286. https://doi.org/10.31614/cmc.2018.04005

Abstract

With the development of adaptive optics and post restore processing techniques, large aperture ground-based telescopes can obtain high-resolution images (HRIs) of targets. The pose of the space target can be estimated from HRIs by several methods. As the target features obtained from the image are unstable, it is difficult to use existing methods for pose estimation. In this paper a method based on real-time target model matching to estimate the pose of space targets is proposed. First, the physically-constrained iterative deconvolution algorithm is used to obtain HRIs of the space target. Second, according to the 3D model, the ephemeris data, the observation time of the target, and the optical parameters of the telescope, the simulated observation image of the target in orbit is rendered by a scene simulation program. Finally, the target model searches through yaw, pitch, and roll until the correlation between the simulated observation image and the actual observation image shows an optimal match. The simulation results show that the proposed pose estimation method can converge to the local optimal value with an estimation error of about 1.6349°.

Keywords

Ground-based telescope, pose estimation, correlation matching, space target, image restoration.

Cite This Article

Li, Z., Wang, J., Chen, T., Wang, B., Wu, Y. (2018). Pose Estimation of Space Targets Based on Model Matching for Large-Aperture Ground-Based Telescopes. CMES-Computer Modeling in Engineering & Sciences, 117(2), 271–286.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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