In this paper, a real WiFi fingerprint-based indoor localization system is considered, where three primary components including the APP in smart phone, the server system and the embedded localization algorithm, have been designed. This paper proposes a dedicated data preprocessing algorithm to solve the singular-collection problem. Furthermore, the issue of WiFi access point (AP) missing is discussed and the theoretical analysis is presented under the condition of a two-AP scenario. Finally, because of unequal amount of location information contained in received signal strength (RSS) from different AP, the weighted RSS (WRSS) and the iterative weighted K nearest neighbor (IWKNN) algorithm are proposed for localization. Experimental results shows the proposed scheme achieves a competitive localization accuracy.


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    Title :

    WiFi Fingerprint Based Indoor Localization with Iterative Weighted KNN for WiFi AP Missing


    Contributors:
    Wang, Donglin (author) / Zhao, Feng (author) / Wang, Ting (author) / Zhang, Xuetao (author)


    Publication date :

    2018-08-01


    Size :

    7576349 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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