Sequential learning for fingerprint based indoor localization

被引：5
|
作者：
Nhan Vo Than Ngo [1 ]
Kim, Jeong Geun [1 ]
机构：
[1] Kyung Hee Univ, Coll Elect & Informat, Dept Elect Engn, Yongin, South Korea
来源：
AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS | 2017年 / 71卷
基金：
新加坡国家研究基金会;
关键词：
Indoor localization; Convex optimization; Fingerprinting;
D O I：
10.1016/j.aeue.2016.10.023
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we introduce a novel approach for improving performance of fingerprinting based indoor localization. Our proposal is a two-step procedure in which severe variation in the received signal strength is minimized during the first step via convex optimization, and distance metric learning is then used to estimate a more accurate location. Numerical results show that our proposal outperforms existing techniques in terms of accuracy and reliability. (C) 2016 Elsevier GmbH. All rights reserved.
引用
收藏
页码：105 / 109
页数：5
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