Advanced integration of WIFI and inertial navigation systems for indoor mobile positioning
EURASIP Journal on Applied Signal Processing
A step counter service for Java-enabled devices using a built-in accelerometer
Proceedings of the 1st International Workshop on Context-Aware Middleware and Services: affiliated with the 4th International Conference on Communication System Software and Middleware (COMSWARE 2009)
RF-Based Initialisation for Inertial Pedestrian Tracking
Pervasive '09 Proceedings of the 7th International Conference on Pervasive Computing
Simultaneous localization and mapping for pedestrians using only foot-mounted inertial sensors
Proceedings of the 11th international conference on Ubiquitous computing
Sparsetrack: enhancing indoor pedestrian tracking with sparse infrastructure support
INFOCOM'10 Proceedings of the 29th conference on Information communications
Towards mobile phone localization without war-driving
INFOCOM'10 Proceedings of the 29th conference on Information communications
Did you see Bob?: human localization using mobile phones
Proceedings of the sixteenth annual international conference on Mobile computing and networking
Tasking networked CCTV cameras and mobile phones to identify and localize multiple people
Proceedings of the 12th ACM international conference on Ubiquitous computing
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Particle filters for positioning, navigation, and tracking
IEEE Transactions on Signal Processing
A reliable and accurate indoor localization method using phone inertial sensors
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Improved actionSLAM for long-term indoor tracking with wearable motion sensors
Proceedings of the 2013 International Symposium on Wearable Computers
Smartphone-based indoor pedestrian tracking using geo-magnetic observations
Mobile Information Systems
Hi-index | 0.00 |
As the use of smartphones spreads rapidly, user localization becomes an important issue for providing diverse location-based services (LBS). While tracking users in outdoor environments is easily done with GPS, the solution for indoor tracking is not trivial. One common technique for indoor user tracking is to employ inertial sensors, but such a system needs to be capable of handling noisy sensors that would normally lead to cumulative locating errors. To reduce such error, additional infrastructure has often been deployed to adjust for these cumulative location errors. As well, previous work has used highly accurate sensors or sensors that are strapped to the body. This paper presents a stand-alone pedestrian tracking system, using only a magnetometer and an accelerometer in a smartphone in indoor corridor environments that are normally laid out in a perpendicular design. Our system provides reasonably accurate pedestrian locations without additional infrastructure or sensors. The experiment results show that the location error is less than approximately 7 m, which is considered adequate for indoor LBS applications.