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    Providing orbit information with predetermined bounded accuracy

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    Author(s)
    Braun, Vitali
    Collection
    Knowledge Unlatched (KU)
    Language
    English
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    Abstract
    The exchange of orbit information is becoming more important in view of the increasing population of objects in space as well as the increase in parties involved in space operations. The aim of this thesis was to investigate how orbit information maintained by a space surveillance system can be provided to its users. Services like collision avoidance require very accurate information, while other services might be less stringent. An approach was studied, which allows to derive orbit and covariance information of predetermined accuracy from a reference orbit. Using Chebyshev polynomials, continuous state vector and covariance matrix information can be provided. The major advantage is that no inter- or extrapolation on the user's side is required. A method to reduce the data amount by interpolating the variance envelope functions was also studied. The proposed method in this thesis gives access to highly accurate information from the catalogue, where this information is required. On the other hand it can also provide less accurate information, where requirements are less restrictive, thereby allowing for a significantly reduced amount of data to be transferred and stored.
    URI
    https://library.oapen.org/handle/20.500.12657/56791
    Keywords
    Computers; Computer Science; Technology & Engineering; Science; Physics
    DOI
    https://doi.org/10.30819/4405
    ISBN
    9783832544058
    Publisher
    Logos Verlag Berlin
    Publisher website
    https://www.logos-verlag.com/
    Publication date and place
    2016
    Grantor
    • Knowledge Unlatched
    Imprint
    Logos Verlag Berlin
    Rights
    https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
    • Harvested from KU

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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