A Neural Network Approach for Radio Frequency Based Indoors Localization

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2012

Autores

Azenha, A (Autor) Outra; Peneda, L (Autor) Outra; Adriano Carvalho (Autor) FEUP

Ata de Conferência Internacional

Título: 38TH ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2012)

Páginas: 5990-5995

38th Annual Conference on IEEE-Industrial-Electronics-Society (IECON )

Montreal, CANADA, OCT 25-28, 2012

Indexação

ISI Web of Knowledge - 6 Citações

Scopus - 5 Citações

Outras Informações

ID Authenticus: P-005-427

DOI: 10.1109/iecon.2012.6389103

Abstract (EN): Radio Frequency (RF) based localization is appropriate for indoors quasi-structured environments. However some accuracy issues remain which are raised by the characteristics of localization accuracy requirements. This paper adopts the Artificial Neural Network (ANN) method to overcome a few of them. Making use of available communications subsystem built in wireless protocols, Received Signal Strength Indication (RSSI) can become a measured variable that supplies ANN schemes. RSSI post-processing filters improve localization accuracy and ANNs emulate the required trilateration for indoors RF localization. Preliminary ANN learning results are included in this paper. This promising result encourages further research on ANN learning for indoor localization.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6