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i Beacon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i Beacon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i Beacon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i Beacon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.
In many traditional indoor large space localization method,it is difficult to improve both positioning accuracy and real-time performance.This paper proposes a localization system based on i Beacon network.The system composes of two optimized indoor positioning algorithms,and has an i Beacon 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 i Beacon identification 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 i Beacon 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.
出处
《应用科学学报》
CAS
CSCD
北大核心
2017年第1期51-62,共12页
Journal of Applied Sciences
基金
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
关键词
iBeacon
接收信号强度
室内定位
双层定位
概率匹配
i Beacon
received signal strength indication（RSSI）
indoor positioning
double positioning
probability matching
