期刊名称：International Journal of Computers and Communications
印刷版ISSN：2074-1294
出版年度：2012
卷号：6
期号：2
页码：137-148
出版社：University Press
摘要：Nowadays, advanced mobile devices can obtain current position with the help of positioning data systems such as GPS, GLONASS, Galileo, and so on. In addition cellular network positioning with base station locations or crowd source WIFI positioning approaches are available. However, positioning data sets usually have erroneous data for various reasons, mainly due to the environmental issues as well as inherent systematical issues. While doing research related to positioning data sets, authors experienced quite a large number of erroneous positioning data using Apple iPhone or Samsung Galaxy devices, and thus need to filter evident errors. In this paper, we will suggest relatively simple, but efficient filtering method based on statistical approach. From the user’s mobile positioning data in a form of < latitude; longitude; time > obtained by mobile evices, we can calculate user’s speed and acceleration. From the idea of sliding window (moving window), we can calculate statistical parameters from speed and acceleration of user position data and thus filtering can be made with controllable parameters. We expect that the simplicity of our algorithm can be applied on portable mobile device with low computation power. For the possible enhancement of our method, we will focus on the construction of more precise window for better filtering. A backtracking interpolation was added in order to replace erroneous data with proper estimations in order to have more precise estimation of moving window. We also proposed this filtering algorithm with interpolation as a basis of future investigation in the section of conclusion and future research.
