Abstract Prediction accuracy of debris location in a perturbing environment is measured by the orbit covariance or uncertainty, which can be propagated with linear or nonlinear models. Linear models decline in propagation accuracy while nonlinear models are computationally intensive, thus not well applied for massive debris orbits needing the high precision. Usually, the debris observations are sparse, resulting in the linearly-propagated covariance over-optimistic. After analyzing with Monte Carlo simulation, the statistical characterizations of propagated orbit errors over past and future time are basically the same in terms of error magnitude, which is theoretically expected. For hundreds of thousands of debris, it only needs an accurate and efficient uncertainty propagation method. This paper proposes a method to dynamically calibrate the linearly-propagated covariance using past observations, including three steps in the estimation of initial orbit covariance, linear propagation of the estimated covariance, and dynamic calibration of the propagated covariance using past observations. Experiments of real data processing show that high-precision propagated errors are achieved, with the accuracy improved by more than 70% after calibration. Besides, to facilitate the catalogue of orbit error, an analytical representation of propagated covariance is proposed, which provides error information of the propagated orbit to users for various needs.


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    Titel :

    Accurate propagation of debris orbit error via dynamic calibration and its cataloguing


    Beteiligte:
    Li, Bin (Autor:in) / Sang, Jizhang (Autor:in) / Liu, Hongkang (Autor:in)

    Erschienen in:

    Advances in Space Research ; 63 , 8 ; 2422-2435


    Erscheinungsdatum :

    2018-12-27


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch