title: PPP Sliding Window Algorithm and Its Application in Deformation Monitoring.
abstract: Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts.
authors.affiliation: Research Center of GNSS, Wuhan University, Wuhan, 430079, China.
authors.forename: Weiwei
authors.initials: W
authors.lastname: Song
authors.affiliation: College of Natural Resource and Environment, South China Agricultural University, Guangzhou, 510642, China.|Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation,Guangzhou, 510642, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Zhang
authors.affiliation: School of Geodesy and Geomatics, Wuhan University, Wuhan, 430079, China.
authors.forename: Yibin
authors.initials: Y
authors.lastname: Yao
authors.affiliation: Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China.
authors.forename: Yanyan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Guangdong Province Key Laboratory for Land use and consolidation, Guangzhou, 510642, China.|Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou, 510642, China.
authors.forename: Yuming
authors.initials: Y
authors.lastname: Hu