A Bayesian Approach for RF-Based Indoor Localisation

Widyawan, M. Klepal, D. Pesch
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引用次数: 45

Abstract

The proliferation of Wireless LAN and Wireless Sensor Network make the technologies become an attractive proposition for indoor localisation. Both technologies have provided communication infrastructure and hence RF-based localisation with WLAN and WSN becomes a software-only solution. WLAN-based localisation generally provides room accuracy, therefore sensor data fusion with WSN is proposed when better location accuracy is needed. This paper will describe a Bayesian approach for indoor localisation. A suboptimal sequential Bayesian method of Particle Filter combined with Map Filtering technique is used for sensor data fusion between WLAN and WSN. The location system performance also will be evaluated.
基于射频的室内定位贝叶斯方法
无线局域网和无线传感器网络的普及使得无线定位技术成为室内定位的一个有吸引力的提议。这两种技术都提供了通信基础设施,因此基于射频的无线局域网和无线传感器网络本地化成为一种纯软件解决方案。基于无线局域网的定位通常提供房间精度,因此在需要更好的定位精度时,提出了传感器数据与WSN融合的方法。本文将描述一种用于室内定位的贝叶斯方法。将次优序列贝叶斯粒子滤波方法与地图滤波技术相结合,用于无线局域网与无线传感器网络之间的传感器数据融合。定位系统的性能也将被评估。
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