The enhancement of space-based space situational awareness capability is crucial for coping with the increasingly crowded space environment due to the unique advantageous observation conditions, which requires the improvement of the accuracy of real-time space-based orbit determination for noncooperative space targets. However, the inaccurate positional knowledge of space-based observation platforms has been one of the primary constraints on enhancing orbit determination precision. This work developed a new method of real-time space-based noncooperative orbit determination for cases involving position propagation errors of observation platforms. A state vector augmentation method is proposed based on the observation platform position and velocity errors, and the dynamic system consisting of the augmented state equation and a pinhole camera measurement model based on the pixel coordinates in the image plane of photoelectric sensor is established. The analytic and numeric methods are combined to conduct analysis for the system observability, and the results indicate that the system is observable if the orbital radius time histories of the observation platform and target are different, and the gravitational perturbations can augment the system observability. Then a filter strategy is proposed, in which the extended Kalman filter is reinitialized periodically each time the orbit of the observation platform is redetermined by the ground stations. Simulation results indicate that compared with the conventional filter without the additional state vector, the filter adopting the proposed state vector augmentation significantly improves the target orbit determination accuracy across different orbit propagation error levels of the observation platform, and a target position accuracy of better than 100 m can be achieved.


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    Title :

    Space-Based Noncooperative Orbit Determination Considering Observation Platform Position Error


    Additional title:

    J. Aerosp. Eng.


    Contributors:
    Sun, Xiucong (author) / He, Lixuan (author) / Wang, Yuan (author)

    Published in:

    Publication date :

    2025-09-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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