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Relative attitude estimation for small satellite based on stellar image matching
Author(s): You Zhai; Xiwei Guo; Dong Han; Peng He
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Paper Abstract

Small satellites have a bright prospect in space exploration. One of the bottlenecks in developing small satellites is precise attitude estimation. Therefore, a relative attitude estimation method for small satellite is proposed using the stellar images captured by stellar camera. Essentially, the proposed method determines satellites relative attitude variation by infinite homography, which provides constraints on attitude variation of satellite camera. Homography between stellar images induced by stars is used to approximate the infinite homography which is obtained by matching two stellar images captured by satellite camera at different time. The specific procedure of the proposed method is as follows: First, star points features are extracted for matching by segmentation and non-maxima suppression. Second, star descriptors are constructed in a far larger local region for star points based on Speeded Up Robust Features (SURF) descriptors. Third, nearest neighbor method is used to get candidate correspondent star points and then outliers are rejected with RANSAC based strategy. Finally, relative attitude variation between two stellar images is solved with matched star points using regularized least square method. In order to verify the feasibility of the proposed method, experiments are carried out with simulated stellar images and digital simulation. Simulated stellar image matching experiment shows stars points matching method can get abundant of correspondent stars and the errors are below 1 pixel. Digital simulation shows that the accuracy of relative attitude estimation reaches 0.01° with about 0.5 pixels star location errors. Experiment results indicate that the proposed method is feasible and can precisely determine satellite relative attitude change.

Paper Details

Date Published: 14 August 2019
PDF: 7 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 1117906 (14 August 2019); doi: 10.1117/12.2539639
Show Author Affiliations
You Zhai, Army Engineering Univ. (China)
Xiwei Guo, Army Engineering Univ. (China)
Dong Han, Army Engineering Univ. (China)
Peng He, Army Engineering Univ. (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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