Review of the robustness and applicability of monocular pose estimation systems for relative navigation with an uncooperative spacecraft

• Published in: Progress in aerospace sciences Vol. 110; p. 100548
• Main Authors: Pasqualetto Cassinis, Lorenzo, Fonod, Robert, Gill, Eberhard
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2019; Elsevier BV
• Subjects: Active debris removal; Algorithms; Background noise; Cameras; Image contrast; Image processing; In-orbit servicing; Monocular cameras; Navigation; Orbital rendezvous; Pose estimation; Power consumption; Relative pose estimation; Robustness; Signal to noise ratio; Solvers; Space debris; Space missions; Spacecraft; Visual-based navigation filters; Active debris removal; Monocular cameras; Image processing; Relative pose estimation; Visual-based navigation filters; In-orbit servicing
• ISSN: 0376-0421; 1873-1724
• DOI: 10.1016/j.paerosci.2019.05.008

The relative pose estimation of an inactive target by an active servicer spacecraft is a critical task in the design of current and planned space missions, due to its relevance for close-proximity operations, i.e. the rendezvous with a space debris and/or in-orbit servicing. Pose estimation systems based solely on a monocular camera are recently becoming an attractive alternative to systems based on active sensors or stereo cameras, due to their reduced mass, power consumption and system complexity. In this framework, a review of the robustness and applicability of monocular systems for the pose estimation of an uncooperative spacecraft is provided. Special focus is put on the advantages of multispectral monocular systems as well as on the improved robustness of novel image processing schemes and pose estimation solvers. The limitations and drawbacks of the validation of current pose estimation schemes with synthetic images are further discussed, together with the critical trade-offs for the selection of visual-based navigation filters. The state-of-the-art techniques are analyzed in order to provide an insight into the limitations involved under adverse illumination and orbit scenarios, high image contrast, background noise, and low signal-to-noise ratio, which characterize actual space imagery, and which could jeopardize the image processing algorithms and affect the pose estimation accuracy as well as the navigation filter's robustness. Specifically, a comparative assessment of current solutions is given at different levels of the pose estimation process, in order to bring a novel and broad perspective as compared to previous works.