Abstract

The demand to enhance distance estimation and location accuracy in a variety of Non-Line-of-Sight (NLOS) indoor environments has boosted investigation into infrastructure-less ranging and collaborative positioning approaches. Unfortunately, capturing the required measurements to support such systems is tedious and time-consuming, as it requires simultaneous measurements using multiple mobile devices, and no such database are available in literature. This article presents a Bluetooth Low Energy (BLE) database, including Received-Signal-Strength (RSS) and Ground-Truth (GT) positions, for indoor positioning and ranging applications, using mobile devices as transmitters and receivers. The database is composed of three subsets: one devoted to the calibration in an indoor scenario; one for ranging and collaborative positioning under Non-Line-of-Sight conditions; and one for ranging and collaborative positioning in real office conditions. As a validation of the dataset, a baseline analysis for data visualization, data filtering and collaborative distance estimation applying a path-loss based on the Levenberg-Marquardt Least Squares Trilateration method are included.

Measurement(s)

Received Signal Strength of Bluetooth Low Energy

Technology Type(s)

Bluetooth Low Energy

Factor Type(s)

position

Sample Characteristic - Organism

Mobile devices

Sample Characteristic - Environment

Indoor enviroments

Details

Title
Mobile device-based Bluetooth Low Energy Database for range estimation in indoor environments
Author
Pascacio, Pavel 1   VIAFID ORCID Logo  ; Torres-Sospedra, Joaquín 2   VIAFID ORCID Logo  ; Jiménez, Antonio R. 3   VIAFID ORCID Logo  ; Casteleyn, Sven 4   VIAFID ORCID Logo 

1  Universitat Jaume I, Institute of New Imaging Technologies, Castellón, Spain (GRID:grid.9612.c) (ISNI:0000 0001 1957 9153); Tampere University, Electrical Engineering Unit, Tampere, Finland (GRID:grid.502801.e) (ISNI:0000 0001 2314 6254) 
2  Universidade do Minho, Centro ALGORITMI, Guimarães, Portugal (GRID:grid.10328.38) (ISNI:0000 0001 2159 175X) 
3  Spanish National Research Council (CSIC-UPM), Center for Automation and Robotics, Madrid, Spain (GRID:grid.4711.3) (ISNI:0000 0001 2183 4846) 
4  Universitat Jaume I, Institute of New Imaging Technologies, Castellón, Spain (GRID:grid.9612.c) (ISNI:0000 0001 1957 9153) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-022-01406-2
ProQuest document ID
2674138441
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.