Radio Map Building with IEEE 802.15.4 for Indoor Localization Applications

M. Mamun, David Vera Anaya, Fan Wu, Jean-Michel Redouté, M. Yuce
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引用次数: 6

Abstract

Automated radio map building for Radio Signal Strength (RSS) based fingerprinting localization is implemented in this paper. Fingerprinting technique is composed of an offline phase for collecting geotagged fingerprint data called a radio map and an online phase for location estimation by comparing an unknown object’s location with the radio map. Typically, radio map is created manually by moving and pin-pointing a location while scanning a network for RSS values within a pre-specified pattern. This cumbersome method is very time consuming and results in inaccuracies in the radio map. This paper presents an automated system to build a radio map of indoor environment by using a self-directed car. The car can move, measure 2D distances, collect RSS values and forward the data to a server via a gateway which calculates the car location coordinates. To test and verify the system, an experiment is conducted in our departmental office spaces. The coordinate estimation accuracy and RSS mapping consistency produced by the proposed system make it possible to build a more accurate and realistic radio map for indoor environments in an automated fashion with decreased possibility of human errors.
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基于IEEE 802.15.4的室内定位应用无线地图构建
本文实现了基于无线电信号强度(RSS)的指纹定位自动生成无线地图。指纹识别技术由离线阶段(用于收集称为无线地图的地理标记指纹数据)和在线阶段(通过将未知物体的位置与无线地图进行比较来进行位置估计)组成。通常,无线电地图是通过在预先指定的模式中扫描网络中的RSS值时移动和精确定位一个位置来手动创建的。这种繁琐的方法非常耗时,并导致无线电地图的不准确。本文介绍了一种利用自动驾驶汽车自动绘制室内环境无线地图的系统。汽车可以移动,测量2D距离,收集RSS值,并通过计算汽车位置坐标的网关将数据转发给服务器。为了测试和验证该系统,我们在部门办公空间进行了实验。该系统所产生的坐标估计精度和RSS映射一致性使其能够以自动化的方式构建更准确、更真实的室内环境无线电地图,减少了人为错误的可能性。
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