Abstract
In the process of on-orbit servicing, chasers achieve approach and contact with target spacecraft are via a series of orbital transfer and motion control. However, most target spacecraft are non-cooperative targets. As a matter of fact, mainly technical difficulty of non-cooperative targets still lies in unable directly obtaining their motion parameters, thereby, it is impossible to realize their autonomously rendezvous and capture. Thus, measure motion parameters of non-cooperative targets from outside is significant for research on-orbit service. In this paper, a pose measurement method coupled initial pose measurement with model-based tracking is put forward for space non-cooperative targets. Specifically, an algorithm based on SIFT matching to measure initial pose of target tracking is proposed to start subsequent target tracking. Afterwards, a target tracking algorithm is presented, which is via a priori information and the combination of edge features and point features. As well as, an M estimator is introduced to improve the accuracy and robustness of target tracking algorithm. Finally, an experimental platform is constructed to fulfill experiments to validate the effectiveness of proposed method. Also, the experimental results demonstrate that our approach has highly precision and robustness in vary illuminations. Simultaneously, our method could satisfy the real-time requirement of pose measurement for non-cooperative targets.
Highlights
Capturing non-cooperative targets is indispensable to multitudes of on-orbit missions, such as prolong spacecraft lifespan, assistance faulty spacecraft into pre-selected orbit, and push abandoned satellites into the grave orbit [1]–[3]
Because of space target is sensitive to illumination, occlusion, and view-point variations, while SIFT feature extraction operator has better adaptability to these factors, an algorithm based on SIFT matching to measure initial pose of target tracking is proposed to initial the subsequent target tracking, which flow path is summarized as follows, VOLUME 7, 2019
In order to measure initial pose of target tracking, our algorithm has three important parts, respectively are, reference pose measurement of non-cooperative target in query image, extract and matching SIFT feature points between query image and current image, and pose solution based on multipoint matching
Summary
Capturing non-cooperative targets is indispensable to multitudes of on-orbit missions, such as prolong spacecraft lifespan, assistance faulty spacecraft into pre-selected orbit, and push abandoned satellites into the grave orbit [1]–[3]. Due to state of motion is unknown, research difficulty on capturing noncooperative targets still lies in accurate estimation of the motion parameters [4]–[7]. To address this issue, researchers come up with quite a few solutions. DLR designed a capture mechanism for non-cooperative target orbit engines, and presented a complex noncooperative target recognition algorithm based on multisensor data fusion [8]. This method was fully controlled from ground system.
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