Improve GPS Positioning Accuracy with Context Awareness
This paper presents an approach to calibrate GPS position by using the context awareness technique from the Pervasive Computing. Previous researches on GPS calibration mostly focus on the methods of integrating auxiliary hardware so that the user’s context information and the basic demand of the user are ignored. From the inspiration of the pervasive computing research, this paper proposes a novel approach, called PGPS (Perceptive GPS), to directly improve GPS positioning accuracy from the contextual information of received GPS data. PGPS is started with sampling received GPS data to learning carrier’s behavior and building a transition probability matrix based upon HMM (Hidden Markov Model) model and Newton’s Laws. After constructing the required matrix, PGPS then can interactively rectify received GPS data in real time. That is, based on the transition matrix and received online GPS data, PGPS infers the behavior of GPS carrier to verify the rationality of received GPS data. If the received GPS data deviate from the inferred position, the received GPS data is then dropped. Finally, an experiment was conducted and its preliminary result shows that the proposed approach can effectively improve the accuracy of GPS position.
Context awareness Pervasive Computing GPS Newtons Laws Markov Model Maximum Likelihood Function
Jiung-yao Huang Chung-Hsien Tsai
Dept.of Computer Science and Information Engineering,National Taipei University Dept.of Computer Science and Information Engineering,National Central University
国际会议
The First IEEE International Conference on Ubi-Media Coputing and Workshops(第一届泛媒体处理国际会议)
兰州
英文
2008-07-15（万方平台首次上网日期，不代表论文的发表时间）