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

机译:通过使用Wi-Fi直接设备的密集Wi-Fi直接网络中的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:一种迭代算法,其提出了一种基于其他跟踪对象的估计位置估计跟踪对象的位置的迭代算法。该方法通过使用来自已知接入点的Wi-Fi无线电信号强度指示符(RSSI)来估计所有跟踪对象(客户端)的位置。然后,接入点最近的受试者将被评为下次迭代的接入点。迭代过程停止,直到电流和先前估计之间的估计差小于阈值。添加了卡尔曼滤波器以最小化不规则RSSI的影响。所提出的方法需要在跟踪区域中足够数量的客户端。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设施。

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