Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device

Research on Visual Measurement for Spacecraft Rendezvous and Approach

Author RenXingXing
Tutor QuZuoShen
School Harbin Institute of Technology
Course Control Science and Engineering
Keywords Space rendezvous and approach Feature extraction Pose measurement Object tracking
CLC TP391.41
Type Master's thesis
Year 2008
Downloads 162
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Space rendezvous and approach technology is the key technology in Space Rendezvous and Docking (RVD). It determines the success of the rendezvous and docking process. At present, visual measurement technology based on CCD camera is a hot topic. In this thesis, an in-depth study on the key technology including visual measurement algorithm for spacecraft rendezvous and approach based on cooperative target, object detection and tracking based on non-cooperative target, and the visual measurement system are developed.First, in terms of actual application, the space rendezvous and approach process based on cooperative target is systematically studied. The images are segmented with thresholding techniques and a method of converse searching is designed to detect the features and realize the cursor sets switch. After judging the validity of the extracted points by prior knowledge, the P3P algorithm and pose solution algorithm are employed to calculate the 6-DOF pose relation between the target and the tracking spacecraft.Second, algorithm of vision detection and tracking based on non-cooperative target is studied. On account of special optic features, kinds of feature detection and filter prediction are combined to solve the problem. The detection of lines and corners are combined to get the original features, an area centered with these features is used for the SIFT detection. The eigenvectors with maximal gradient modular is considered as the expression of the non-cooperative target. A Kalman filter is utilized to estimate the next locations of these features. Then SIFT matching algorithm is used to get new SIFT eigenvectors which are considered as matching results.At last, based on the semi-physical simulation platform, the vision subsystem of cooperative target measurement and non-cooperative target detection and tracking is constructed. And the system performances are detailed evaluated according to the experiment data. The experiment results demonstrate that the algorithms meet the requirements of precision, stability, and real time. Meanwhile, the system can be expanded easily.

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