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Indoor positioning through an iterative method in dense Wi-Fi-direct networks with Wi-Fi direct devices

机译:在带有Wi-Fi Direct设备的密集Wi-Fi-direct网络中通过迭代方法进行室内定位

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An iterative algorithm that estimates the position of tracked subjects based on the estimated position of other tracked subjects nearer to the reference points is proposed. The method starts by estimating the position of all tracked subjects (client) by trilateration using Wi-Fi radio signal strength indicators (RSSI) from known Access Points. Subjects nearest to the access points will then be possibly rated as the access points for next iteration. The iteration process stops until the estimation difference between current and previous estimates is less than a threshold value. Kalman filter is added to minimize the impact of irregular RSSI. The proposed method requires sufficient number of clients in the tracked area. The method could be implemented on a mobile device within existing Wi-Fi network without the need for additional devices or infrastructure.
机译:提出了一种迭代算法,该算法基于其他更靠近参考点的被跟踪对象的估计位置来估计被跟踪对象的位置。该方法首先使用来自已知接入点的Wi-Fi无线电信号强度指示器(RSSI)通过三边测量估算所有被跟踪对象(客户)的位置。然后,最接近访问点的主题可能会被评定为下一次迭代的访问点。迭代过程停止,直到当前估计值与先前估计值之间的估计差小于阈值为止。添加了卡尔曼滤波器,以最大程度地减少不规则RSSI的影响。所提出的方法需要在跟踪区域中有足够数量的客户。该方法可以在现有Wi-Fi网络内的移动设备上实现,而无需其他设备或基础架构。

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