Landmark-assisted location and tracking in outdoor mobile network

Modern mobile devices integrating sensors, like accelerometers and cameras, are paving the way to the definition of high-quality and accurate geolocation solutions based on the informations acquired by these sensors, and data collected and managed by GSM/3G networks. In this paper, we present a tech...

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Bibliographic Details
Published in:Multimedia tools and applications 2012-07, Vol.59 (1), p.89-111
Main Authors: Anisetti, Marco, Ardagna, Claudio A., Bellandi, Valerio, Damiani, Ernesto, Döller, Mario, Stegmaier, Florian, Rabl, Tilmann, Kosch, Harald, Brunie, Lionel
Format: Article
Language:English
Subjects:
Accelerometers
Accuracy
Algorithms
Analysis
Antennas
Cameras
Candidates
Computer Communication Networks
Computer Science
Correlation analysis
Data Structures and Information Theory
Digital cameras
Geographic information systems
Infrastructure
Landmarks
Location based services
Mobile communication systems
Multimedia Information Systems
Networks
Position (location)
Sensors
Special Purpose and Application-Based Systems
Studies
Wireless networks
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Summary:Modern mobile devices integrating sensors, like accelerometers and cameras, are paving the way to the definition of high-quality and accurate geolocation solutions based on the informations acquired by these sensors, and data collected and managed by GSM/3G networks. In this paper, we present a technique that provides geolocation and mobility prediction of mobile devices, mixing the location information acquired with the GSM/3G infrastructure and the results of a landmark matching achieved thanks to the camera integrated on the mobile devices. Our geolocation approach is based on an advanced Time-Forwarding algorithm and on database correlation technique over Received Signal Strength Indication (RSSI) data, and integrates information produced by a landmark recognition infrastructure, to enhance algorithm performances in those areas with poor signal and low accurate geolocation. Performances of the algorithm are evaluated on real data from a complex urban environment.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-010-0721-x