This study tests the hypothesis that orbiting data centers equipped with a deep-learning computer vision pipeline can achieve sub-minute information freshness suitable for real-time wildfire detection, and confirms that orbital edge computing can deliver the such level of timeliness for near-instantaneous environmental monitoring.
The geosynchronous orbit (GEO) region hosts critical high-value satellites, making continuous space situational awareness essential for collision risk assessment and national security. We propose a model for quantitatively evaluating the performance and gain of ground-based optical telescope networks for GEO observatio...
Dong-Bo Che, Kainan Yao, Jianli Wang et al.· Applied Optics· 0 citations
As low-Earth orbit (LEO) satellites are increasingly equipped with highly precise Global Navigation Satellite Systems (GNSS) receivers, new opportunities for GNSS-based precise orbit determination (POD) arise. The availability of GNSS observations from satellites that are geometrically well distributed over the entire...
Lukas Müller, Markus Rothacher, Benedikt Soja et al.· Journal of Geodesy· 0 citations
The Earth Observation Satellite Scheduling Problem (EOSSP) has seen significant algorithmic
advances, yet the lack of standardized, open-source benchmarks has hindered fair comparison
across studies. Recent large-scale benchmark suites have begun addressing this gap by
providing high-fidelity simulation environments, b...
Tubolayefa Warekuromor· International Journal of Mod...· 0 citations
To enable global connectivity through 6G, the efficient operation of hierarchical satellite networks that integrate geostationary (GEO) and low-earth orbit (LEO) satellites is paramount. A significant challenge in achieving this operational efficiency lies in the dynamic association between the extensive array of LEO s...
Kazuma Mashiko, Hiroaki Hashida, Y. Kawamoto et al.· IEEE Transactions on Cogniti...· 0 citations
With the rapid development of aerospace technology and the large-scale deployment of low Earth orbit (LEO) constellations, the risk of orbital collisions has increased, creating a growing demand for reliable observations of satellite maneuvers. However, public datasets containing real maneuver records remain scarce. We...
This paper investigates the feasibility of a decentralized alternative where data gathered from a global network of amateur astronomers is classified using a machine learning model that automatically detects satellite trails in telescope imagery, providing position updates at higher frequency and lower costs than conve...
Jay Zhang· International Journal of Ene...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
