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Measures of Nonlinearity and non-Gaussianity in Orbital Uncertainty Propagation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43956250" target="_blank" >RIV/49777513:23520/19:43956250 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/9011445" target="_blank" >https://ieeexplore.ieee.org/document/9011445</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Measures of Nonlinearity and non-Gaussianity in Orbital Uncertainty Propagation

  • Original language description

    Orbit uncertainty propagation (OUP) is an important tracking problem appearing in space situational awareness. The uncertainty, which is initially approximately Gaussian, is transformed by the time propagation and eventually becomes non-Gaussian. Gaussian representation of the uncertainty becomes gradually inaccurate, which is often addressed by splitting the Gaussian representation into a mixture of Gaussian densities (GM), which can describe the uncertainty with arbitrary accuracy. Measures of nonlinearity (MoNL) and non-Gaussianity (MoNG) assess the degree of the model nonlinearity around a working point and thus they pose a convenient means to indicate time instants suitable for the splitting. The paper provides an analysis of several MoNLs and MoNGs with a special focus on their behavior in the OUP from the numerical, theoretical, and practical points of view. Based on the analysis, measures eligible for governing the splitting in the OUP based on GM are recommended.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 2019 22th International Conference on Information Fusion (FUSION)

  • ISBN

    978-0-9964527-8-6

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    1-8

  • Publisher name

    IEEE

  • Place of publication

    Ottawa, Kanada

  • Event location

    Ottawa, Kanada

  • Event date

    Jul 2, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article