Title :
High-Performance Indoor Localization with Full-Band GSM Fingerprints
Author :
Denby, Bruce ; Oussar, Yacine ; Ahriz, Iness ; Dreyfus, Gérard
Author_Institution :
Univ. Pierre et Marie Curie - Paris VI, Paris, France
Abstract :
GSM trace mobile measurements are used to study indoor handset localization in an urban apartment setting. Nearest-neighbor, support vector machine (SVM), and Gaussian process classifiers are compared. A linear SVM is found to provide mean room-level classification efficiency near 100%, but only when the full set of GSM carriers is used. To our knowledge, this is the first study to use fingerprints containing all GSM carriers, and the first to suggest that GSM could be useful for very high-performance indoor localization.
Keywords :
cellular radio; indoor radio; GSM trace mobile measurement; Gaussian process classifiers; full-band GSM fingerprint; high-performance indoor localization; indoor handset localization; mean room-level classification efficiency; support vector machine; urban apartment setting; Databases; Fingerprint recognition; GSM; Global Positioning System; Nuclear magnetic resonance; Position measurement; Support vector machine classification; Support vector machines; Telephone sets; Testing;
Conference_Titel :
Communications Workshops, 2009. ICC Workshops 2009. IEEE International Conference on
Conference_Location :
Dresden
Print_ISBN :
978-1-4244-3437-4
DOI :
10.1109/ICCW.2009.5207991