Advanced support vector machines for 802.11 indoor location
Signal Processing
Smartphone-based Wi-Fi tracking system exploiting the RSS peak to overcome the RSS variance problem
Pervasive and Mobile Computing
Beacon selection for localisation in IEEE 802.11 wireless infrastructure
International Journal of Ad Hoc and Ubiquitous Computing
Beacon selection for localisation in IEEE 802.11 wireless infrastructure
International Journal of Ad Hoc and Ubiquitous Computing
Smartphone-based indoor pedestrian tracking using geo-magnetic observations
Mobile Information Systems
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Indoor location systems based on IEEE 802.11b (WiFi) mobile devices often rely on the received signal strength indicator to estimate the user position. Two key characteristics of these systems have not yet been fully analyzed, namely, the temporal and spatial sampling process required to adequately describe the distribution of the electromagnetic field in indoor scenarios; and the device calibration, necessary for supporting different mobile devices within the same system. By using a previously proposed nonparametric methodology for system comparison, we first analyzed the time-space sampling requirements for WiFi indoor location systems in terms of conventional sampling theory and system performance. We also proposed and benchmarked three new algorithms for device calibration, with increasing levels of complexity and performance. We conclude that feasible time and space sampling rates can be used, and that calibration algorithms make possible the handling of previously unknown mobile devices in the system.