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Decision Tree Approach to Estimate User Location in WLAN Based on Location Fingerprinting

机译:基于位置指纹识别的WLAN中估算用户位置的决策树方法

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The estimation of user location using modern communication technology like WLAN based on Radio Signal Strength, is a recent interesting area. There are many indoor positioning techniques to estimate user location; Location Fingerprinting, Time of Arrival (TOA), Time Difference of Arrival (TDOA), Angle of Arrival (AOA) and others. Location Fingerprinting technique is more suitable than other techniques, because TOA, TDOA or AOA is suffer from non-line-of-sight error and multi path, especially in urban and suburban area. In this paper we study the fingerprinting technique using Neural Network, Nearest Neighbor and Decision Tree to estimate the location. The results of the experiment show that using DT technique is the best to estimate the location of the user.
机译:基于无线电信号强度的WLAN等现代通信技术估计用户位置是最近有趣的区域。有许多室内定位技术来估计用户位置;位置指纹识别,到达时间(TOA),到达时间差(TDOA),到达角度(AOA)等。位置指纹技术比其他技术更适合,因为TOA,TDOA或AOA遭受非视线误差和多路径,特别是在城市和郊区。在本文中,我们使用神经网络,最近邻和决策树来估计位置的指纹识别技术。实验结果表明,使用DT技术是最好估计用户的位置。

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