Abstract

Autonomous rendezvous and docking (ARD) plays a very important role in planned space programs, the success of ARD rests with the estimation accuracy and efficiency of relative pose among various spacecraft in rendezvous and docking. In this paper, a high accuracy and efficiency estimation algorithm of relative pose of cooperative space targets is presented based on monocular vision imaging, in which a modified gravity model approach and multiple targets tracking methods are employed to improve the accuracy of feature extraction and enhance the estimation efficiency, meanwhile the Levenberg–Marquardt method (LMM) is used to achieve a well global convergence. Moreover an experimental platform with DSP and FPGA is designed and implemented. The comprehensive experimental results demonstrate its outstanding accuracy and efficiency, the update rate achieves 16Hz and the estimated error of depth does not exceed 2% with noise influence.

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