Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

Trainingless fingerprinting-based indoor positioning algorithms with Smartphones using electromagnetic propagation models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Bisio, I. ; Dept. of Naval, Electr., Electron., & Telecommun. Eng., Univ. of Genoa, Genova, Italy ; Lavagetto, F. ; Marchese, Mario ; Pastorino, M.
more authors

Recent multimedia and location-based services (LBSs) employ information about location, orientation, and context of a mobile device. Moreover, the wide spread adoption of Smartphones, usually equipped with powerful processors, accelerometers, compasses, and Global and Hybrid Positioning Systems (GPS/HPSs) receivers, has favored the increasing of location- and context-based services over the last years. In this work a Wi-Fi fingerprint-based indoor positioning techniques is considered. It is aimed at supporting possible location aware services. The main novelty introduced in this paper concerns the training phase, which is usually needed by these techniques. In our approach, the training phase is avoided, since opportune simulative propagation models of the environment in which the algorithm are working are introduced. The resulting technique allows exploiting the accuracy of the fingerprinting approaches and, simultaneously, avoids the heavy training phase, which represents one of the main drawbacks of such techniques.

Published in:

Imaging Systems and Techniques (IST), 2012 IEEE International Conference on

Date of Conference:

16-17 July 2012