ROBUST ESTIMATION FOR SATELLITE SWARMS IN PRESENCE OF OUTLIERS
Pedari, Yasaman
Pedari, Yasaman
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Abstract
The article presents a fresh approach to estimate the position and velocity of satellite swarms in Low Earth Orbit (LEO) while dealing with statistical outliers in sensor measurements. The method builds on the Robust Generalized Maximum Likelihood Kalman Filter (RGMKF) and relies on minimal sensor setup and inter-satellite communication. The framework assumes that all formation satellites have access to GPS through high-altitude navigation satellites and are equipped with sensors to estimate the relative position of neighboring satellites. By leveraging these sensors, the framework can maintain reasonable accuracy when GPS signals are absent or unreliable and improve estimation accuracy when GPS signals are reliable.
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Date
2023-01-01
Student Status
Graduate
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Poster Presentation
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Electrical Engineering
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College of Engineering and Mathematical Sciences
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Engineering and Math Science