MEJORANDO Y FOMENTANDO LA VIDA ACTIVA Y BIENESTAR DESDE EL SENSADO A LA ANALITICA DE DATOS
PID2019-105470RB-C31
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Nombre agencia financiadora Agencia Estatal de Investigación
Acrónimo agencia financiadora AEI
Programa Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i
Subprograma Subprograma Estatal de Generación de Conocimiento
Convocatoria Proyectos I+D
Año convocatoria 2019
Unidad de gestión Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020
Centro beneficiario UNIVERSIDAD DE LA IGLESIA DE DEUSTO
Identificador persistente http://dx.doi.org/10.13039/501100011033
Publicaciones
Resultados totales (Incluyendo duplicados): 1
Encontrada(s) 1 página(s)
Encontrada(s) 1 página(s)
Towards sub-meter level UWB indoor localization using body wearable sensors
Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
- Otim, Timothy
- Bahillo, Alfonso
- Enrique Díez, Luis
- López Iturri, Peio
- Falcone Lanas, Francisco
Thanks to its ability to provide sub-meter level positioning accuracy, Ultrawideband (UWB) has found wide use in several wireless body area network (WBAN) applications such as ambient assisted living, remote patient management and preventive care, among others. In spite of the attractiveness of UWB, it is not possible to achieve this level of accuracy when the human body obstructs the wireless channel, leading to a bias in the Time of Flight (TOF) measurements, and hence a detection of position errors of several meters. In this paper, a study of how a sub-meter level of accuracy can be achieved after compensating for body shadowing is presented. Using a Particle Filter (PF), we apply UWB ranging error models that take into consideration the body shadowing effect and evaluate them through simulations and extensive measurements. The results show a significant reduction in the median position error of up to 75 % and 82 % for simulations and experiments, respectively, leading to the achievement of a sub-meter level of localization accuracy., This work was supported in part by the Research Training Grants Program of the University of Deusto, in part by the Spanish Ministry of Science and Innovation under the PeaceOfMind project (ref. PID2019-105470RB-C31), and in part by the project RTI2018-095499-B-C31, funded by Ministerio de Ciencia, Innovacion y Universidades, Gobierno de Espana (MCIU/AEI/FEDER,UE).