LOCATE-US: Indoor Positioning for Mobile Devices Using Encoded Ultrasonic Signals, Inertial Sensors and Graph-Matching.

Android application indoor LPS inertial measurements sensor fusion smartphone positioning ultrasonic signals

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
10 Mar 2021
Historique:
received: 27 01 2021
revised: 06 03 2021
accepted: 08 03 2021
entrez: 3 4 2021
pubmed: 4 4 2021
medline: 4 4 2021
Statut: epublish

Résumé

Indoor positioning remains a challenge and, despite much research and development carried out in the last decade, there is still no standard as with the Global Navigation Satellite Systems (GNSS) outdoors. This paper presents an indoor positioning system called LOCATE-US with adjustable granularity for use with commercial mobile devices, such as smartphones or tablets. LOCATE-US is privacy-oriented and allows every device to compute its own position by fusing ultrasonic, inertial sensor measurements and map information. Ultrasonic Local Positioning Systems (U-LPS) based on encoded signals are placed in critical zones that require an accuracy below a few decimeters to correct the accumulated drift errors of the inertial measurements. These systems are well suited to work at room level as walls confine acoustic waves inside. To avoid audible artifacts, the U-LPS emission is set at 41.67 kHz, and an ultrasonic acquisition module with reduced dimensions is attached to the mobile device through the USB port to capture signals. Processing in the mobile device involves an improved Time Differences of Arrival (TDOA) estimation that is fused with the measurements from an external inertial sensor to obtain real-time location and trajectory display at a 10 Hz rate. Graph-matching has also been included, considering available prior knowledge about the navigation scenario. This kind of device is an adequate platform for Location-Based Services (LBS), enabling applications such as augmented reality, guiding applications, or people monitoring and assistance. The system architecture can easily incorporate new sensors in the future, such as UWB, RFiD or others.

Identifiants

pubmed: 33802216
pii: s21061950
doi: 10.3390/s21061950
pmc: PMC8001629
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Junta de Comunidades de Castilla-La Mancha
ID : FrailCheck project, SBPLY/17/180501/000392
Organisme : Comunidad de Madrid
ID : CM/JIN/2019-043
Organisme : Ministerio de Ciencia, Innovación y Universidades
ID : RTI2018-095168-B-C51, PID2019-105470RA-C33

Références

Sensors (Basel). 2020 Jul 22;20(15):
pubmed: 32707987
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pubmed: 31013888
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Sensors (Basel). 2018 May 01;18(5):
pubmed: 29724003
Sensors (Basel). 2019 Jan 17;19(2):
pubmed: 30658458

Auteurs

David Gualda (D)

Department of Electronics, University of Alcalá, Alcalá de Henares, 28801 Madrid, Spain.
Signal Theory and Communications Department, King Juan Carlos University, Móstoles, 28933 Madrid, Spain.

María Carmen Pérez-Rubio (MC)

Department of Electronics, University of Alcalá, Alcalá de Henares, 28801 Madrid, Spain.

Jesús Ureña (J)

Department of Electronics, University of Alcalá, Alcalá de Henares, 28801 Madrid, Spain.

Sergio Pérez-Bachiller (S)

Department of Electronics, University of Alcalá, Alcalá de Henares, 28801 Madrid, Spain.

José Manuel Villadangos (JM)

Department of Electronics, University of Alcalá, Alcalá de Henares, 28801 Madrid, Spain.

Álvaro Hernández (Á)

Department of Electronics, University of Alcalá, Alcalá de Henares, 28801 Madrid, Spain.

Juan Jesús García (JJ)

Department of Electronics, University of Alcalá, Alcalá de Henares, 28801 Madrid, Spain.

Ana Jiménez (A)

Department of Electronics, University of Alcalá, Alcalá de Henares, 28801 Madrid, Spain.

Classifications MeSH