Based on data fusion technology, multi-sensor fusion positioning merges several positioning sources together to achieve an optimal positioning result by making full use of all the homogeneous or heterogeneous information from different fusion sensors. However, there has not been much research carried out about the effectiveness evaluation of multi-sensor fusion positioning system. In this paper, a self-feedback effectiveness evaluation algorithm is proposed which can not only evaluate multi-sensor fusion positioning systems, but also improve positioning performance by adopting feedback information. Besides traditional evaluation parameters, confidence level and plug and play capability are proposed as new evaluation parameters to estimate effectiveness of multi-sensor fusion positioning system. Simulations verify the efficiency of proposed evaluation parameters and self-feedback effectiveness evaluation algorithm.


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    Titel :

    Multi-Parameter Based Self-Feedback Effectiveness Evaluation in a Multi-Sensor Fusion Positioning System


    Beteiligte:
    Zhao, Wanlong (Autor:in) / Meng, Weixiao (Autor:in) / Han, Shuai (Autor:in) / Hu, Rose Qingyang (Autor:in)


    Erscheinungsdatum :

    01.09.2017


    Format / Umfang :

    700002 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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