A Constrained Kalman Filter for Wi-Fi-Based Indoor Localization with Flexible Space Organization

被引：3

作者：

Sircoulomb, Vincent ^{[1
]}

Chafouk, Houcine ^{[1
]}

机构：

[1] Normandie Univ, UNIROUEN, IRSEEM, ESIGELEC, F-76000 Rouen, France

来源：

SENSORS | 2022年 / 22卷 / 02期

关键词：

constrained Kalman filtering; Wi-Fi; Localization Based Service (LBS); flexible indoor organization; ALGORITHM; TRACKING;

D O I：

10.3390/s22020428

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

This paper presents a constrained Kalman filter for Wi-Fi-based indoor localization. The contribution of this work is to introduce constraints on the object speed and to provide a numerically optimized form for fast computation. The proposed approach is suitable to flexible space organization, as in warehouses, and when objects can be spun around, for example barcode readers in a hand. We experimented with the proposed technique using a robot and three devices, on five different journeys, in a 6000 m(2) warehouse equipped with six Wi-Fi access points. The results highlight that the proposed approach provides a 19% improvement in localization accuracy.

引用

页数：14

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