A group of unmanned aerial vehicles (UAVs) can efficiently obtain the information of an unknown target or location of interest. Efficacy of localization gets enhanced if UAVs form an optimal formation geometry around the target. This work presents a unified scheme of cooperative localization and tracking for a group of fixed-wing unmanned aerial vehicles. The sensors having different types and qualities are mounted on each UAV to form a heterogeneous sensing network. These UAVs are used to localize a moving target with unknown states. The performance of an unbiased estimator can be quantified by the Cramer–Rao lower bound, which is the same as the inverse of Fisher information. In this work, the conditions of optimal UAV formations are derived to maximize the Fisher information of the unknown target. Next, a generalized protocol is presented to result in the desired formations around the moving target that maximizes the information of the target. A cooperative localization algorithm is used to localize the unknown target states using the noisy measurements obtained from the heterogeneous sensing network. The efficacy of the proposed unified framework is illustrated with numerical examples.


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    Title :

    Information-Rich Formation Tracking: A Unified Scheme of Cooperative Control and Localization


    Contributors:

    Published in:

    Publication date :

    2020-08-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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