Sensing and classifying impairments of GPS reception on mobile devices

Authors:
Henrik Blunck;Mikkel Baun Kjærgaard;Thomas Skjødeberg Toftegaard
Affiliations:
Department of Computer Science, Aarhus University, Denmark;Department of Computer Science, Aarhus University, Denmark;Department of Computer Science, Aarhus University, Denmark
Venue:
Pervasive'11 Proceedings of the 9th international conference on Pervasive computing
Year:
2011

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Abstract

Positioning using GPS receivers is a primary sensing modality in many areas of pervasive computing. However, previous work has not considered how people's body impacts the availability and accuracy of GPS positioning and for means to sense such impacts. We present results that the GPS performance degradation on modern smart phones for different hand grip styles and body placements can cause signal strength drops as high as 10-16 dB and double the positioning error. Furthermore, existing phone applications designed to help users identify sources of GPS performance impairment are restricted to show raw signal statistics. To help both users as well as application systems in understanding and mitigating body and environment-induced effects, we propose a method for sensing the current sources of GPS reception impairment in terms of body, urban and indoor conditions. We present results that show that the proposed autonomous method can identify and differentiate such sources, and thus also user environments and phone postures, with reasonable accuracy, while relying solely on GPS receiver data as it is available on most modern smart phones.