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
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;
Conference_Titel :
Wireless Communication Systems (ISWCS), 2012 International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4673-0761-1
Electronic_ISBN :
2154-0217
DOI :
10.1109/ISWCS.2012.6328446
