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  • Open Access

    ARTICLE

    Ensembling Neural Networks for User’s Indoor Localization Using Magnetic Field Data from Smartphones

    Imran Ashraf, Soojung Hur, Yousaf Bin Zikria, Yongwan Park*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2597-2620, 2021, DOI:10.32604/cmc.2021.016214 - 13 April 2021

    Abstract Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors: Smartphone heterogeneity and smaller data lengths. The use of multifarious smartphones cripples the performance of such approaches owing to the variability of the magnetic field data. In the same vein, smaller lengths of magnetic field data decrease the localization accuracy substantially. The current study proposes the use of multiple neural networks like deep neural network (DNN), long short term memory network (LSTM), and gated recurrent unit network (GRN) to perform indoor localization based on the embedded magnetic sensor of… More >

  • Open Access

    ARTICLE

    MFPL: Multi-Frequency Phase Difference Combination Based Device-Free Localization

    Zengshan Tian1, Weiqin Yang1, Yue Jin1, Liangbo Xie1, *, Zhengwen Huang2

    CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 861-876, 2020, DOI:10.32604/cmc.2020.07297

    Abstract With the popularity of indoor wireless network, device-free indoor localization has attracted more and more attention. Unlike device-based localization where the target is required to carry an active transmitter, their frequent signal scanning consumes a large amount of energy, which is inconvenient for devices with limited energy. In this work, we propose the MFPL, device-free localization (DFL) system based on WiFi distance measurement. First, we combine multi-subcarrier characteristic of Channel State Information (CSI) with classical Fresnel reflection model to get the linear relationship between the change of the length of reflection path and the subcarrier… More >

  • Open Access

    ARTICLE

    Improved GNSS Cooperation Positioning Algorithm for Indoor Localization

    Taoyun Zhou1,2, Baowang Lian1, Siqing Yang2,*, Yi Zhang1, Yangyang Liu1,3

    CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 225-245, 2018, DOI:10.3970/cmc.2018.02671

    Abstract For situations such as indoor and underground parking lots in which satellite signals are obstructed, GNSS cooperative positioning can be used to achieve high-precision positioning with the assistance of cooperative nodes. Here we study the cooperative positioning of two static nodes, node 1 is placed on the roof of the building and the satellite observation is ideal, node 2 is placed on the indoor windowsill where the occlusion situation is more serious, we mainly study how to locate node 2 with the assistance of node 1. Firstly, the two cooperative nodes are located with pseudo-range… More >

  • Open Access

    ARTICLE

    Localization Algorithm of Indoor Wi-Fi Access Points Based on Signal Strength Relative Relationship and Region Division

    Wenyan Liu1, Xiangyang Luo1,*, Yimin Liu1, Jianqiang Liu2, Minghao Liu1, Yun Q. Shi3

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 71-93, 2018, DOI:10.3970/cmc.2018.055.071

    Abstract Precise localization techniques for indoor Wi-Fi access points (APs) have important application in the security inspection. However, due to the interference of environment factors such as multipath propagation and NLOS (Non-Line-of-Sight), the existing methods for localization indoor Wi-Fi access points based on RSS ranging tend to have lower accuracy as the RSS (Received Signal Strength) is difficult to accurately measure. Therefore, the localization algorithm of indoor Wi-Fi access points based on the signal strength relative relationship and region division is proposed in this paper. The algorithm hierarchically divide the room where the target Wi-Fi AP… More >

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