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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Jianying Wang,Haizhao Liang,Hui Liu,Dong Ye,Zhaowei Sun.Relative Attitude and Position Estimation for Spacecraft from Multiple Geometric Features[J].Journal of Harbin Institute Of Technology(New Series),2016,23(2):87-96.DOI:10.11916/j.issn.1005-9113.2016.02.013.
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Relative Attitude and Position Estimation for Spacecraft from Multiple Geometric Features
Author NameAffiliation
Jianying Wang Science and Technology on Space Physics Laboratory, Beijing 100076, China 
Haizhao Liang Beijing Institute of Long March Vehicle, Beijing 100076, China 
Hui Liu Science and Technology on Space Physics Laboratory, Beijing 100076, China 
Dong Ye Research Center of Satellite Technology, Harbin Institute of Technology,Harbin 150001, China. 
Zhaowei Sun Research Center of Satellite Technology, Harbin Institute of Technology,Harbin 150001, China. 
Abstract:
This paper investigates the pose and motion estimation problem using single camera measurement for spacecraft. The leader spacecraft of three-dimensional shape is observed by a calibrated camera fixed on the follower spacecraft. Based on dual numbers, an integrated observation model is proposed based on a combination of multiple geometric features including points, lines and circles, which can improve the robustness and accuracy of the estimation algorithm. A six-degree-of-freedom relative motion model is proposed by using the dual quaternion representation, in which the rotation-translation coupling effect due to the points deviating from the center of the mass is described. Employing the proposed observation model and dynamics model, an Extended Kalman Filter is presented to estimate the relative state between the two spacecraft. Numerical simulations are performed to evaluate the proposed approaches, showing the convergence of relative estimation errors and superior estimation performance.
Key words:  dual quaternion  coupled dynamics  vision-based estimation  Kalman filtering
DOI:10.11916/j.issn.1005-9113.2016.02.013
Clc Number:TP391.7
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