Robust Monte Carlo localization for mobile robots
Artificial Intelligence
A Statistical Modeling Approach to Location Estimation
IEEE Transactions on Mobile Computing
Practical robust localization over large-scale 802.11 wireless networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
International Journal of Robotics Research
Location Estimation via Support Vector Regression
IEEE Transactions on Mobile Computing
The SkyLoc Floor Localization System
PERCOM '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications
Pervasive and Mobile Computing
BeTelGeuse: A Platform for Gathering and Processing Situational Data
IEEE Pervasive Computing
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Accurate GSM indoor localization
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Mobility detection using everyday GSM traces
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Practical metropolitan-scale positioning for GSM phones
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
IEEE Communications Magazine
Enriching location information: an energy-efficient approach
Proceedings of the 13th international conference on Ubiquitous computing
Challenges for social sensing using WiFi signals
Proceedings of the 1st ACM workshop on Mobile systems for computational social science
AWESOM: automatic discrete partitioning of indoor spaces for wifi fingerprinting
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
Accelerometer-based transportation mode detection on smartphones
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
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We propose a grid-based GSM positioning algorithm that can be deployed entirely on mobile devices. The algorithm uses Gaussian distributions to model signal intensity variations within each grid cell. Position estimates are calculated by combining a probabilistic centroid algorithm with particle filtering. In addition to presenting the positioning algorithm, we describe methods that can be used to create, update and maintain radio maps on a mobile device. We have implemented the positioning algorithm on Nokia S60 and Nokia N900 devices and we evaluate the algorithm using a combination of offline and real world tests. The results indicate that the accuracy of our method is comparable to state-of-the-art methods, while at the same time having significantly smaller storage requirements.