Hidden Markov model-based 3D path-matching using raytracing-generated Wi-Fi models

Author

Viol, N. ; Link, J.A.B. ; Wirtz, Hanno ; Rothe, D. ; Wehrle, Klaus

Author_Institution

Commun. & Distrib. Syst., RWTH Aachen Univ., Aachen, Germany

fYear

2012

fDate

13-15 Nov. 2012

Firstpage

1

Lastpage

10

Abstract

We propose an efficient approach to probabilistic 3D indoor path-matching and localization based on Wi-Fi-signal measurements using Hidden Markov Model-based (HMM) algorithms. Given a 3D model of the building, we derive high-resolution emission probabilities and transition probabilities from raytracing-generated Wi-Fi signal propagations. Therefore we use both the generated signal-strength values and the geometric information of the 3D model. Based on the emission and transition probabilities and a sequence of Wi-Fi signal measurements provided by the client, the HMM-based algorithm computes the most probable path through the building.

Keywords

hidden Markov models; indoor communication; probability; ray tracing; solid modelling; structural engineering; wireless LAN; 3D model; HMM algorithms; HMM-based algorithm; building; generated signal-strength values; geometric information; hidden Markov model-based 3D path-matching; hidden Markov model-based algorithms; high-resolution emission probability; indoor localization; probabilistic 3D indoor path-matching; raytracing-generated wi-fi models; transition probability; wi-fi signal propagations; wi-fi-signal measurements; Accuracy; Computational modeling; Hidden Markov models; IEEE 802.11 Standards; Radio propagation; Signal resolution; Solid modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Indoor Positioning and Indoor Navigation (IPIN), 2012 International Conference on

Conference_Location

Sydney, NSW

Print_ISBN

978-1-4673-1955-3

Type

conf

DOI

10.1109/IPIN.2012.6418873

Filename

6418873