DocumentCode
1710203
Title
Fast, handset-based GSM fingerprints for indoor localization
Author
Tian, Ye ; Denby, Bruce ; Ahriz, Iness ; Roussel, Pierre ; Dreyfus, Gérard
Author_Institution
SIGMA Lab. & Univ. Pierre et Marie Curie, Paris, France
fYear
2012
Firstpage
641
Lastpage
645
Abstract
Accurately localizing users in indoor environments remains an important and challenging task. The article presents new results on room-level indoor localization, using cellular Received Signal Strength fingerprints collected with a standard cellular handset programmed to perform fast scans of the 900 and 1800 Megahertz GSM bands as a user explores an indoor environment at a normal walking pace. Support Vector Machines are used to deal with the high dimensionality of the fingerprints. The study demonstrates that an appropriately programmed standard cellular handset can provide a simple, inexpensive solution for accurate room-level indoor localization.
Keywords
cellular radio; indoor radio; radio direction-finding; support vector machines; telecommunication computing; cellular received signal strength fingerprints; fingerprint dimensionality; frequency 1800 MHz; frequency 900 MHz; handset-based GSM fingerprints; indoor environment; room-level indoor localization; standard cellular handset; support vector machines; Classification algorithms; Fingerprint recognition; GSM; Kernel; Laboratories; Support vector machines; Training; fingerprint; indoor; localization; machine learning; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communication Systems (ISWCS), 2012 International Symposium on
Conference_Location
Paris
ISSN
2154-0217
Print_ISBN
978-1-4673-0761-1
Electronic_ISBN
2154-0217
Type
conf
DOI
10.1109/ISWCS.2012.6328446
Filename
6328446
Link To Document