This work investigates the problem of joint localization and target tracking (JLATT) of multi-vehicle systems (MVSs) in the presence of Byzantine attacks (BAs). For MVSs, there may exist malicious and misbehaving vehicles, called Byzantine vehicles, which act as deceivers and pass false information to their neighbors. For the first time, we formulate a resilient JLATT framework to synthesize the hybrid problems of distributed cooperative localization and flock tracking in the presence of BAs. More specifically, we propose a covariance weighted mean-subsequence-filter (CW-MSF) algorithm to guarantee that the MVS achieves flock tracking w.r.t a target even in the presence of a certain fraction of Byzantine vehicles. Note that this resilient JLATT scheme does not require global information and thus it is fully distributed. The practicality and validity of this novel JLATT framework are verified via an illustrative numerical simulation example.


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    Title :

    Byzantine Resilient Joint Localization and Target Tracking of Multi-Vehicle Systems


    Contributors:
    Cui, Yukang (author) / Jia, Yachao (author) / Li, Yuman (author) / Shen, Jun (author) / Huang, Tingwen (author) / Gong, Xin (author)

    Published in:

    Publication date :

    2023-04-01


    Size :

    1956597 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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