iBeacon网络下的区域化双层定位体系

发布时间：2018-06-10 21:13

本文选题：iBeacon + 接收信号强度　；参考：《应用科学学报》2017年01期

【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.
[Abstract]:Aiming at the problem that it is difficult for many traditional indoor large space positioning methods to improve the real-time and precision of location simultaneously, a regionalized double-layer positioning system based on I Beacon network is proposed. The system consists of two optimized indoor localization algorithms and I Beacon double layer positioning architecture. The former uses the spatial regionalization probability matching algorithm to realize the fast region location, uses the weighted centroid algorithm in the region to realize the high-precision localization in the region, and the latter uses the I Beacon identification code to divide the location nodes into two levels. Different combinations of two-level nodes are used to realize different positioning levels. The system combines two indoor positioning algorithms at different positioning levels through the I Beacon double layer positioning architecture, which can improve the real-time and accuracy at the same time. The experimental results show that the real-time performance of the proposed algorithm is 55.29% and 54.18% higher than that of K-nearest neighbor algorithm and weighted K-nearest neighbor algorithm, respectively. The positioning accuracy is 37.35% higher than the improved weighted centroid algorithm based on RSSI. The system has the advantages of high precision and low cost. It can be widely used in indoor navigation and pedestrian track detection of large buildings, and has high economic and social application value.
【作者单位】：上海大学微电子研究与开发中心;上海大学通信与信息工程学院;
【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
【分类号】：TN925

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