Por favor, use este identificador para citar o enlazar este ítem: http://cybertesis.uni.edu.pe/handle/uni/3267
Título : Spatial statistical analysis for the design of indoor particle-filter-based localization mechanisms
Autor : Martínez-Gómez, Jesus
Martínez del Horno, Miguel
Castillo-Cara, Manuel
Brea Luján, Víctor Manuel
Orozco Barbosa, Luis
García-Varea, Ismael
Palabras clave : Localization;Mobile devices;Signal processing;Model fitting;Wireless local area networks;Spatial analysis
Fecha de publicación : ago-2016
Editorial : Hindawi Publishing Corporation
URI Relacionado: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984889419&doi=10.1177%2f1550147716661953&partnerID=40&md5=ecea0769133f70c3dd4c5ad51e76f51e
Resumen : The accurate localization of end-users and resources is seen as one of the main pillars toward the successful implementation of context-based applications. While current outdoor localization mechanisms fulfill most application requirements, the design of accurate indoor localization mechanisms is still an open issue. Most research efforts are focusing on the design of mechanisms making use of the receiver signal strength indications generated by WLAN (wireless local area network) devices. However, the accuracy and robustness of such mechanisms can be severely compromised due to the random and unpredictable nature of radio channels. In this article, we develop a methodology incorporating various algorithms capable of coping with the unpredictable nature of radio channels. Following a holistic approach, we start by identifying the wireless equipment parameter setting, better meeting the implementation requirements of a robust indoor localization mechanism. We then make use of RANdom SAmple Consensus paradigm: a robust model-fitting mechanism capable of smoothing the data captured during the space survey. Using an experimental setup, we evaluate the benefits of integrating the floor plan and an ordinary Kriging interpolation algorithm in the estimation process. Our main findings show that our proposal can greatly improve the quality of the information to be used in the development of particle-filter-based indoor localization mechanisms.
URI : http://cybertesis.uni.edu.pe/handle/uni/3267
ISSN : 15501329
Correo electrónico : luis.orozco@uclm.es
Derechos: info:eu-repo/semantics/embargoedAccess
Aparece en las colecciones: Instituto General de Investigación

Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
Spatial statistical analysis for the design of indoor particle-filter-based localization mechanisms.pdf154,78 kBAdobe PDFVisualizar/Abrir


Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons Creative Commons