Given partial observation of a space object, the admissible region is defined as the set of all physically acceptable orbits that are consistent with the observation. Given additional constraints on the object's orbital semimajor axis and eccentricity, the admissible region can be further constrained, resulting in the constrained admissible region. All points within that region are traditionally treated as equally likely and are used to initialize a multihypothesis filter. In this paper, known statistics of the measurement process as well as space object population semimajor axis and eccentricity values are used to obtain a more representative distribution over the constrained region. This nonuniform distribution results in faster convergence of the multihypothesis filter because unlikely hypotheses are promptly eliminated. It is also shown how known statistics in inclination and right ascension of the ascending node can be included to incorporate additional constraints on other orbital parameters. The probabilistic admissible region is a thorough approach to orbit initiation in Bayesian tracking within the context of multihypothesis filtering. Noting that the concepts presented in this paper can be applied to many measurement scenarios, the idea is illustrated using a short-arc, angles-only observation scenario. Presented at the 2015 AIAA Astrodynamics Specialist Conference, Vail, CO, 9-13 August 2015


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Probabilistic Admissible Region for Multihypothesis Filter Initialization




    Publication date :

    2017




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    55.54 Flugführung
    Local classification TIB:    770/7040