Spatio-temporal adaptive indoor positioning using an ensemble approach

被引：6

作者：

Hayashi, Taisei ^{[1
]}

Taniuchi, Daisuke ^{[1
]}

Korpela, Joseph ^{[1
]}

Maekawa, Takuya ^{[1
]}

机构：

[1] Osaka Univ, Dept Multimedia Engn, Grad Sch Informat Sci & Technol, 1-5 Yamadaoka, Suita, Osaka 5650871, Japan

来源：

PERVASIVE AND MOBILE COMPUTING | 2017年 / 41卷

关键词：

Indoor positioning; Wi-Fi sensing; Fingerprinting; Ensemble learning;

D O I：

10.1016/j.pmcj.2016.12.001

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a fingerprinting-based Wi-Fi indoor positioning method robust against temporal fluctuations and spatial instability in Wi-Fi signals. An ensemble is created using randomized weak position estimators, with the estimators specialized to different areas in the target environment and designed so that each area has estimators that rely on different subsets of stable APs. When conducting positioning, we cope with spatial instability by dynamically adjusting the weights of the weak estimators depending on the user's estimated location and cope with temporal fluctuations by dynamically adjusting the weights based on a periodic assessment of their performance using a particle filter tracker. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：319 / 332

页数：14

共 29 条

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