Sample-based computation of the joint-time probability of collision motivates developing the Mahalanobis Shell Sampling (MSS) algorithm, which samples nondegenerate normal random variables, enabling rare event simulation without unduly penalizing sample size. The MSS method has unbiased estimators in sample mean and covariance, and it may achieve arbitrary precision when approximating probability measures. For Clohessy–Wiltshire relative orbital dynamics, computational MSS exponential rates of error convergence (in the mean-square-error sense) are shown to improve by one order of magnitude (for sample mean and covariance) over Monte Carlo; when reproducing the instantaneous probability of collision, MSS has a comparable mean-square-error convergence rate performance to Monte Carlo.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Stochastic Convergence of Sobol-Based Mahalanobis Shell Sampling Collision Probability Computation


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    01.05.2023




    Medientyp :

    Aufsatz (Konferenz) , Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Mahalanobis Shell Sampling (MSS) Method for Collision Probability Computation

    Nunez Garzon, Ulises E. / Lightsey, E Glenn | AIAA | 2021


    MAHALANOBIS SHELL SAMPLING (MSS) METHOD FOR COLLISION PROBABILITY COMPUTATION

    Garzon, Ulises E. Nunez / Lightsey, E Glenn | TIBKAT | 2021



    FAST PROBABILITY-OF-COLLISION COMPUTATION

    GUPTA UJJWAL DAS / LESIV ROSTYSLAV / SAUND BRADLEY LARKIN et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Fast and Reliable Computation of Instantaneous Orbital Collision Probability

    Masson, Matthieu / Arzelier, Denis / Bréhard, Florent et al. | AIAA | 2024