Tracking clustered satellites in the presence of noisy measurements creates a scenario where satellites are likely to be cross-tagged. This work focuses on the identity management of a closely spaced set of CubeSats immediately after a deployment. The main contribution is an identity management process that augments the generalized labeled multi-Bernoulli filter to probabilistically handle identity assignments. The effectiveness of the method is demonstrated on simulated tracking data from the 88 Planet Labs Flock 3 CubeSats deployed on PSLV-C37. Simulation results indicate that the proposed identity management process can effectively establish identities within 3 days after deployment.


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    Title :

    Identity Management of Clustered Satellites with a Generalized Labeled Multi-Bernoulli Filter


    Contributors:

    Published in:

    Publication date :

    2020-06-24


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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