Practical robust localization over large-scale 802.11 wireless networks
Proceedings of the 10th annual international conference on Mobile computing and networking
The Horus WLAN location determination system
Proceedings of the 3rd international conference on Mobile systems, applications, and services
PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
Zone-based rss reporting for location fingerprinting
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
A taxonomy for radio location fingerprinting
LoCA'07 Proceedings of the 3rd international conference on Location-and context-awareness
Automatic mitigation of sensor variations for signal strength based location systems
LoCA'06 Proceedings of the Second international conference on Location- and Context-Awareness
Accurate GSM indoor localization
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
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
Movement-aware and QoS-driven indoor location and mobile service discovery framework
International Journal of Wireless and Mobile Computing
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Heterogeneous wireless clients measure signal strength differently. This is a fundamental problem for indoor location fingerprinting, and it has a high impact on the positioning accuracy. Mapping-based solutions have been presented that require manual and error-prone calibration for each new client. This article presents hyperbolic location fingerprinting, which records fingerprints as signal strength ratios between pairs of base stations instead of absolute signal strength values. This article also presents an automatic mapping-based method that avoids calibration by learning from online measurements. The evaluation shows that the solutions can address the signal strength heterogeneity problem without requiring extra manual calibration.