Noise filter method for mobile trajectory data
Compared with common data sets such as vehicle GPS and POI punch-in data, mobile trajectory data more specifically records people's real travel conditions. However, due to the lack of accuracy of the acquisition equipment, compared with the use of more professional GPS positioning equipment, mobile trajectory data has more data errors and lacks. Therefore, more data preprocessing steps are required before the mobile trajectory data is put into practical use. This chapter summarizes various existing techniques for noise removal of trajectory data, including mean filtering, median filtering, Kalman filtering, particle swarm filtering, and road network matching. In addition, the effect of trajectory filtering on mobile trajectory data is shown.
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|Department||Department of Computer Science and Engineering|
1.SUSTech-UTokyo Joint Research Center on Super Smart City,Department of Computer Science and Engineering,Southern University of Science and Technology (SUSTech),Shenzhen,China
2.School of Urban Planning and Design,Peking University,Shenzhen,China
|First Author Affilication||Department of Computer Science and Engineering|
Feng，Defan,Zhang，Haoran,Song，Xuan. Noise filter method for mobile trajectory data. 2023-01-01.
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