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Monitoring Structural Displacements on a Wall with Five-Constellation Precise Point Positioning: A Position-Constrained Method and the Performance Analyses.

Authors :
Chu, Feng-Yu
Chen, Yin-Wei
Source :
Remote Sensing. Mar2023, Vol. 15 Issue 5, p1314. 21p.
Publication Year :
2023

Abstract

The global navigation satellite system (GNSS) precise point positioning (PPP) technique has been commonly applied to structural displacement monitoring. Considering the sheltering effect, GNSS receivers are regularly mounted on the top of a structure, but the structure is often not a rigid body; therefore, the receiver should also be mounted on the wall of the structure. Combining five constellations, GNSS can effectively reduce the sheltering effect. Therefore, this study attempts to apply the five-constellation PPP technique to monitor structural long-term displacements on the wall (SLDW) and structural vibrational displacements on the wall (SVDW) and then analyze their performance. Two novel methods are proposed in monitoring SVDW. Firstly, semi-generated measurements are designed to generate pseudo-environments with vibrations for the receiver. Therefore, additional instruments are not necessary to generate vibrations. Secondly, to further reduce the sheltering effect, a position-constrained PPP (PCPPP) model is developed. Formal performance analyses are presented in this study, and the results show that using the five-constellation PPP to monitor SLDW and SVDW in the horizontal direction is possible as long as the sheltering effect over the half sky of the receiver is not severe. In monitoring SVDW, the PCPPP model can perform better than the classical PPP model and be successful in the horizontal direction when the condition of elevation cutoff is given as high as 50°. For Asia-Pacific mid-low-latitude regions, the global positioning system (GPS) and BeiDou system (BDS) are important to maintain the availability of monitoring SVDW. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
5
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
162384738
Full Text :
https://doi.org/10.3390/rs15051314