Composcan: adaptive scanning for efficient concurrent communications and positioning with 802.11
Proceedings of the 6th international conference on Mobile systems, applications, and services
Unsupervised Learning for Solving RSS Hardware Variance Problem in WiFi Localization
Mobile Networks and Applications
A calibration-free localization solution for handling signal strength variance
MELT'09 Proceedings of the 2nd international conference on Mobile entity localization and tracking in GPS-less environments
Cramér-Rao bound analysis of localization using signal strength difference as location fingerprint
INFOCOM'10 Proceedings of the 29th conference on Information communications
Indoor location fingerprinting with heterogeneous clients
Pervasive and Mobile Computing
Review: A survey of active and passive indoor localisation systems
Computer Communications
Smartphone-based Wi-Fi tracking system exploiting the RSS peak to overcome the RSS variance problem
Pervasive and Mobile Computing
A Multisensor Architecture Providing Location-based Services for Smartphones
Mobile Networks and Applications
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Differences in signal strength among wireless network cards, phones and tags are a fundamental problem for location fingerprinting. Current solutions require manual and error-prone calibration for each new client to address this problem. This paper proposes hyperbolic location fingerprinting, which records fingerprints as signal-strength ratios between pairs of base stations instead of absolute signal-strength values. The proposed solution has been evaluated by extending two well-known location fingerprinting techniques to hyperbolic location fingerprinting. The extended techniques have been tested on ten-hour-long signal-strength traces collected with five different IEEE 802.11 network cards. The evaluation shows that the proposed solution solves the signal-strength difference problem without requiring extra manual calibration and provides a performance equal to that of existing manual solutions.