A Radio-Map clustering Algorithm for RSS based Localization using Directional Antennas

A. Nagy, Thomas Bigler, A. Treytl, T. Sauter
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引用次数: 8

Abstract

Position determination of nodes in wireless networks is becoming a prerequisite in industrial environments to fulfill various application and network needs ranging from device localization to safety or real-time behavior. Received Signal Strength (RSS) based localization techniques have been a research topic for many years, yet suffer from various physical effects. Usage of directed antennas could increase the localization performance and suppress disturbing effects, yet dramatically increase the complexity of localization especially in large scale networks. In this paper we propose a machine-learning aided approach for clustering the RSS map that significantly optimizes the position estimation of nodes in environments with antennas having arbitrary antenna patterns.
一种基于定向天线的RSS定位无线电地图聚类算法
无线网络中节点的位置确定正在成为工业环境中满足各种应用和网络需求的先决条件,从设备定位到安全或实时行为。基于接收信号强度(RSS)的定位技术是多年来的研究课题,但受到各种物理效应的影响。定向天线的使用可以提高定位性能,抑制干扰效应,但也极大地增加了定位的复杂性,特别是在大规模网络中。在本文中,我们提出了一种机器学习辅助的RSS地图聚类方法,该方法可以显着优化具有任意天线方向图的天线环境中节点的位置估计。
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