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On-orbit recognition of resident space objects by using star trackers
Acta Astronautica, 2020Abstract The paper focuses on the opportunity to use star sensors to help space situational awareness and space surveillance. Catalogs of orbiting satellites around Earth are usually established on ground-based measurements that rely on optical or radar data provided by instruments on Earth.
D. Spiller +6 more
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Multi-Bistatic Radar for Resident Space Objects Feature Estimation
2018 19th International Radar Symposium (IRS), 2018The amount of space debris orbiting the Earth has seen a dramatic grow through the recent years. Its rising population increases the potential danger to space missions. At present time, it is urgent to gain as much information as possible in order to characterize this environment.
Ghio, S., Martorella, M.
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A comparison of Radon domain approaches for resident space object’s parameter estimation
2020 21st International Radar Symposium (IRS), 2020The amount of space debris orbiting around the Earth has seen a dramatic growth through the recent years. This growth is fed by an avalanche multiplication process. In fact, according to the “Kessler syndrome”, any collision generates more debris that then collide with other objects and produce further debris.
Ghio S., Martorella M.
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Simulation of resident space objects detection from space-based optical imaging
Sensors and Systems for Space Applications XIII, 2020The United States Space Surveillance Network catalogs around 23,000 Resident Space Objects (RSOs). The completeness of their coverage of the true RSO population decreases gradually with object size and radar reflectivity. While the population of cm level space debris is poorly represented in the catalogs these space bullets can cause severe damage to ...
Maxime Vernier +3 more
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Resident Space Object Characterization Using Polarized Light Curves
Journal of Guidance, Control, and Dynamics, 2023Light curves, or the time-history of photometric brightness, have previously been demonstrated to allow for estimation of a space object’s attitude, shape, and surface parameters. However, these methods are subject to many limitations, including the need for accurate initial estimates to initialize filters, and the inability to regularly estimate ...
Andrew D. Dianetti, John L. Crassidis
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In-Orbit Tracking of Resident Space Objects: A Comparison of Monocular and Stereoscopic Vision
IEEE Transactions on Aerospace and Electronic Systems, 2014This paper develops new methods for vision-based satellite attitude control aimed at space-based optical tracking of resident space objects (RSOs). An Earth-orbiting chaser satellite equipped with either one or two body-fixed cameras can successfully track an RSO provided that the target is kept within the camera field of view.
Shai Segal, Pini Gurfil, Kamran Shahid
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Contributions of the OH Airglow to Resident Space Object Irradiance
2005Abstract : A goal of space situational awareness is the detection and characterization of resident space objects. An around-the-clock capability depends on the ability to observe the space object under a variety of illumination conditions. In this report, we focus on space-based sensors operating in the visible, near-infrared and short-wave infrared ...
James W. Duff, John Gruninger
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Proximity Operations Testing with a Rotating and Translating Resident Space Object
AIAA Guidance, Navigation, and Control Conference, 2009Hardware-In-The-Loop (HWIL) test results using guidance, navigation, and control software to perform the proximity operations between a noncooperative rotating and translating Resident Space Object (RSO) and an Agile Space Vehicle (ASV) are presented.
Jeremiah DiMatteo +3 more
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A Cython Bound Tracklet- Tracklet Correlation for Resident Space Objects
2023 IEEE Aerospace Conference, 2023Rack, Kathrin +6 more
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Astrometric Data for Early Time Series Classification of Resident Space Objects
Journal of Aerospace Information SystemsThe classification of resident space objects (RSOs) is crucial for space situational awareness due to its importance in national defense and the rapid growth of commercially launched RSOs. Machine learning (ML) and deep learning (DL) techniques now facilitate classification of RSOs based on sensor observations; however, they are often constrained by ...
Giovanni Lavezzi +7 more
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