1. Mobility Episode Discovery in the Mobile Networks Based on Enhanced Switching Kalman Filter
- Author
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Toivo Vajakas, Eero Vainikko, Tanel Kiis, Amnir Hadachi, Institute of Computer Science [University of Tartu, Estonie], and University of Tartu
- Subjects
050210 logistics & transportation ,Computer science ,Maximum likelihood ,05 social sciences ,Real-time computing ,Measure (physics) ,02 engineering and technology ,Kalman filter ,Radio networks ,020204 information systems ,0502 economics and business ,0202 electrical engineering, electronic engineering, information engineering ,Time switching ,[INFO]Computer Science [cs] ,Switching Kalman filter ,ComputingMilieux_MISCELLANEOUS - Abstract
The usage of mobile phones has become an important activity in our lives. The passive mobile positioning of mobiles provides large-scale data about human mobility. Hence, in this paper, we are presenting a technique based on continuous time switching Kalman filter to efficiently detect stop and move episodes. The technique has practical and theoretical advantages as the model is more closely related to measure human mobility characteristics and less sensitive to variations in radio network operations. The technique was tested on real radio network data and the results indicated significant improvement with respect to the model performance and the literature.
- Published
- 2018
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