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应用科学学报 ›› 2017, Vol. 35 ›› Issue (1): 51-62.doi: 10.3969/j.issn.0255-8297.2017.01.006

• 通信工程 • 上一篇    下一篇

iBeacon网络下的区域化双层定位体系

姚维强1, 张金艺1,2, 鲍深1, 梁滨2   

  1. 1. 上海大学 微电子研究与开发中心, 上海 200072;
    2. 上海大学 通信与信息工程学院, 上海 200444
  • 收稿日期:2016-07-28 修回日期:2016-10-19 出版日期:2017-01-30 发布日期:2017-01-30
  • 作者简介:张金艺,研究员,研究方向:通信类SoC设计与室内无线定位技术,E-mail:zhangjinyi@staff.shu.edu.cn
  • 基金资助:

    国家“863”高技术研究发展计划基金（No.2013AA03A1121，No.2013AA03A1122）；上海市教委重点学科基金（No.J50104）；上海市科委项目培育基金（No.D.72-0107-00-024）资助

Localization of Double Layer Location System Based on IBeacon Network

YAO Wei-qiang1, ZHANG Jin-yi1,2, BAO Shen1, LIANG Bin2   

  1. 1. Microelectronic Research and Development Center, Shanghai University, Shanghai 200072, China;
    2. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
  • Received:2016-07-28 Revised:2016-10-19 Online:2017-01-30 Published:2017-01-30

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摘要：

针对许多传统室内大空间定位方法难以同时提高定位实时性和精度的问题，提出一种iBeacon网络下的区域化双层定位体系.该体系由两种优化后的室内定位算法与iBeacon双层定位架构组成.前者通过空间区域化概率匹配算法实现快速区域定位，利用区域内加权质心算法实现高精度区域内定位；后者通过iBeacon识别码对定位节点进行两级划分，利用两级节点的不同组合实现不同的定位层次.该体系通过iBeacon双层定位架构将处于不同定位层次的两种室内定位算法相结合，可同时提升实时性和精度.实验表明，在相近定位精度条件下，所提定位体系的实时性比K最近邻算法、加权K最近邻算法分别提高55.29%和54.18%.定位精度比基于RSSI的四边测距改进加权质心算法提高37.35%.该体系具有高精度和低成本优势，可广泛用于大型建筑室内导航及行人轨迹探测等领域，经济和社会应用价值高.

关键词: 接收信号强度, 室内定位, 双层定位, 概率匹配, iBeacon

Abstract:

In many traditional indoor large space localization method, it is difcult to improve both positioning accuracy and real-time performance.This paper proposes a localization system based on iBeacon network.The system composes of two optimized indoor positioning algorithms, and has an iBeacon dual layer positioning architecture.The former achieves rapid location with an algorithm that matchesa region of space probability, and achieves high precision within each region in the area with a weighted centroid algorithm.The latter, based on the iBeacon identifcation code, is divided into two levels of node localization.Different levels of positioning is achieved by using different combinations of these nodes.In the positioning process, the system uses the iBeacon double layer positioning architecture at different levels of the two positioning algorithms to improve accuracy of real-time positioning.Experimental results show that, with similar accuracy, the proposed system improves the real-time performance by 55.29% and 54.18% respectively compared with K-nearest neighbor (KNN) and weighted K-nearest neighbor (WKNN).Positioning accuracy is improved by 37.35% compared with an improved weighted centroid algorithm based on RSSI.The proposed system has high economic and social values as it can be used for navigation in large buildings and detect pedestrian paths.

Key words: iBeacon, indoor positioning, received signal strength indication (RSSI), probability matching, double positioning

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