Resident Space Objects (RSO) include satellites, spacecrafts, and other equipment remaining in Earth's orbit for an extended period following activities such as space launches, orbital missions and collisions, thereby posing a formidable threat to space infrastructure and operations due to the large uncertainty of their population, trajectories, mass, size, etc. It is therefore necessary not only to track the total number of objects in space, but also to continuously estimate the trajectory of these objects and probability of accidental collisions with other objects. At present, RSO are tracked and catalogued using ground-based observations, but Space-Based Space Surveillance (SBSS) represents a valid complementary alternative due to its ability to offer enhanced performances in terms of sensor resolution, tracking accuracy, and weather independence. Accurate and continuous orbit determination of RSO is essential for establishing a unique scheme for an accurate prediction of the RSO dynamics for applications like Point-To-Point Suborbital Transport (PPST) that are envisioned to be commercialized in future. This article proposes an innovative trajectory estimation algorithm through Data Fusion from multiple Electro-Optical (EO) sensors performing Space-Based Space Surveillance (SBSS). A verification case study is performed on a constellation of Distributed Satellite Systems (DSS) that aim to carry out a piggy-backed mission by performing SBSS and Earth observation operations simultaneously.


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    Titel :

    Real Time Non-Cooperative Surveillance of Resident Space Objects Using Estimation-Based Measurement Association


    Beteiligte:


    Erscheinungsdatum :

    03.06.2024


    Format / Umfang :

    927763 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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