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- W4313491133 abstract "In the modern space age, private companies are crowding the already-congested low Earth orbit (LEO) regime with small satellite mega constellations. With over 25,000 objects larger than 10 cm already in LEO, this rapid expansion is forcing us towards the enterprise on Space Traffic Management (STM). STM is an operational effort that focuses on conjunction assessment and collision avoidance between objects. While the equations of motion for objects in orbit are well-known, there are many uncertain parameters that result in the uncertainty of an object's future position. The force that the atmosphere exerts on satellite - known as drag - is the largest source of uncertainty in LEO. This is largely due to the difficulty in predicting mass density in the thermosphere - the neutral region in Earth's upper atmosphere. Presently, most thermosphere models are deterministic and the treatment of uncertainty in density is highly simplified or nonexistent in operations." @default.
- W4313491133 created "2023-01-06" @default.
- W4313491133 creator A5024412615 @default.
- W4313491133 date "2023-01-04" @default.
- W4313491133 modified "2023-09-26" @default.
- W4313491133 title "Probabilistic Space Weather Modeling and Forecasting for the Challenge of Orbital Drag in Space Traffic Management" @default.
- W4313491133 doi "https://doi.org/10.33915/etd.11600" @default.
- W4313491133 hasPublicationYear "2023" @default.
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