RTIL: A Real-Time Indoor Localization System by Using Angle of Arrival of Commodity WiFi Signal

Z. Tian, Zhongchun Wang, Ze Li, Mu Zhou
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引用次数: 5

Abstract

Recently, localization technology using existing infrastructures such as LTE and WiFi networks has advanced greatly. However, localization and tracking using WiFi signal is still challenging since the existing localization systems using Received Signal Strength Indication (RSSI) have limitations such as requiring extensive labor and time costs to construct database. Even for the recent advanced localization systems using Angle of Arrival (AOA) or Time of Flight (TOF), the computational burden and modified protocol limit their deployment. In this paper, we propose RTIL, a real-time indoor localization and tracking system with high accuracy by using commodity WiFi signal. Firstly, we devise a novel algorithm for AOA estimation under condition that the target moves. The proposed AOA estimation algorithm not only calculates AOA using only three antennas without large computational burden and special hardware but also eliminates big AOA error caused by the target's movement. Secondly, to improve the AOA estimation accuracy further we propose a refinement method based on Kalman smoothing. Our implementation and evaluation on the commodity WiFi devices show that RTIL can achieve the 67% localization accuracy of 1.2 m.
基于商用WiFi信号到达角度的实时室内定位系统
近年来,利用LTE和WiFi等现有基础设施的定位技术取得了很大的进步。然而,使用WiFi信号的定位和跟踪仍然具有挑战性,因为现有的使用接收信号强度指示(Received signal Strength Indication, RSSI)的定位系统存在构建数据库需要大量人力和时间成本等局限性。即使对于最近使用到达角(AOA)或飞行时间(TOF)的先进定位系统,计算负担和修改后的协议也限制了它们的部署。本文提出了一种基于商用WiFi信号的高精度室内实时定位跟踪系统RTIL。首先,我们设计了一种新的目标运动条件下的AOA估计算法。所提出的AOA估计算法不仅可以利用三根天线计算AOA,而且可以消除由于目标运动而产生的较大AOA误差。其次,为了进一步提高AOA估计的精度,提出了一种基于卡尔曼平滑的改进方法。我们在商用WiFi设备上的实现和评估表明,RTIL可以达到67%的1.2 m定位精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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