A technology for generation of space object optical image based on 3D point cloud model

LU Tingting; LI Xiao; ZHANG Yao; YAN Yan; YANG Weidong

doi:10.13700/j.bh.1001-5965.2019.0189

Volume 46 Issue 2

Feb. 2020

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Abstract

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Journal of Beijing University of Aeronautics and Astronautics > 2020 > 46(2): 274-286.

Wang Jing, Xi Yang, Han Yonget al. Optimized evaluation point designing for R&D project[J]. Journal of Beijing University of Aeronautics and Astronautics, 2005, 31(05): 556-560. (in Chinese)

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LU Tingting, LI Xiao, ZHANG Yao, et al. A technology for generation of space object optical image based on 3D point cloud model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(2): 274-286. doi: 10.13700/j.bh.1001-5965.2019.0189(in Chinese)

Wang Jing, Xi Yang, Han Yonget al. Optimized evaluation point designing for R&D project[J]. Journal of Beijing University of Aeronautics and Astronautics, 2005, 31(05): 556-560. (in Chinese)

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A technology for generation of space object optical image based on 3D point cloud model

doi: 10.13700/j.bh.1001-5965.2019.0189

1.
Research and Development Department, China Academy of Launch Vehicle Technology, Beijing 100176, China
2.
Key Laboratory of Grain Information Processing and Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China

More Information

Corresponding author: LU Tingting, E-mail:tingtingspring@163.com
Received Date: 28 Apr 2019
Accepted Date: 05 Jul 2019
Publish Date: 20 Feb 2020

Abstract

Abstract

The lack of the prior image data in the space exploration tasks makes it difficult to quantitatively test and evaluate the situation awareness and navigation algorithms based on the optical images. Accordingly, in this paper, we present an algorithm for generating the synthetic space object optical image based on the 3D point cloud model and the basic theory of the projective transformation. First, the 3D point cloud model of the space object and the optical camera model were constructed. Then, the corresponding pairs between all the pixels in the image plane and the space points of the 3D point cloud model were obtained via the basic theory of projective transformation, and subsequently the intensity of each pixel in the image plane was calculated by the lighting direction of its corresponding space point and the Lambertian reflection model, and finally the simulated image was generated. A great deal of simulation experiments demonstrate that the proposed algorithm can produce the more vivid simulated images rapidly than the traditional analytical image generation algorithm, and the generated images can be applied to testing and evaluating the typical space application algorithms qualitatively and quantitatively, such as ellipse fitting, crater detection, optical navigation landing on the planet, automated rendezvous and docking of spacecraft, 3D tracking of spacecraft, and so on.
- space object,
- simulated image,
- point cloud model,
- projective transformation,
- artificial intelligence

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References(27)

References

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