An Improved K-Nearest-Neighbor Indoor Localization Method Based on Spearman Distance

被引：135
|
作者：
Xie, Yaqin [1 ]
Wang, Yan [2 ]
Nallanathan, Arumugam [3 ]
Wang, Lina [1 ]
机构：
[1] Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Meteorol Observat & Signal Proc, Nanjing 210044, Jiangsu, Peoples R China
[2] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China
[3] Kings Coll London, Dept Informat, London WC2R 2LS, England
来源：
IEEE SIGNAL PROCESSING LETTERS | 2016年 / 23卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Indoor localization; RSSI; Spearman distance; Wi-Fi; SEQUENCE-BASED LOCALIZATION;
D O I：
10.1109/LSP.2016.2519607
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：
Indoor localization based on existing Wi-Fi Received Signal Strength Indicator (RSSI) is attractive since it can reuse the existing Wi-Fi infrastructure. However, it suffers from dramatic performance degradation due to multipath signal attenuation and environmental changes. To improve the localization accuracy under the above-mentioned circumstances, an improved Spearman-distance-based K-Nearest-Neighbor (KNN) scheme is proposed. Simulation results demonstrate that our improved method outperforms the original KNN method under the indoor environment with severe multipath fading and temporal dynamics.
引用
收藏
页码：351 / 355
页数：5
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