Post-processing of GNSS data using open source software for structural deformation monitoring

Abstract

In structural deformation monitoring especially of high-rise buildings our main aim is hunting and pin-pointing the deviations of structural movement from reference position (original) and to detect deviancy during normal conditions to catastrophic damage e.g windstorm, thunderstorm, explosion or earthquake. For that to happen an accurate, robust and reliable method for structural monitoring is needed. GNSS with its advanced augmentation techniques can give a positioning accuracy in order of millimetres at its best. Such a higher order of accuracy can be used for precise structural deformation monitoring. Apart from that GNSS gives us loathsome advantages like all weather, around the clock and global coverage. GNSS doesn't need line of sight as it was needed in previous techniques between its stations. Due to these benefits we are using GNSS technology for structural deformation monitoring. GNSS also has some drawbacks like the positioning accuracy is dependent up on number of available satellites, geometry of satellites, multipath and receiver noise. Un-affordable price of precise GNSS receivers also makes it tougher. The data used in the thesis is the one used for structural deformation monitoring with the help of base stations and the rovers using the real time kinematic RTK positioning logged at ICON Tower Karachi, Pakistan a high-rise building. RTKLIB a free software is used for analysis of logged data by applying stand-alone, differential code and differential carrier phase (RTK) positioning techniques. For our post-processing GPS data analysis we had used three rovers at three corners of building story under monitoring with common reference station. One by one on each of the sets we have RTK in RTKPOST GUI application of RTKLIB. For this analysis we have made three cases of comparison between individual RTK results of rover pairs and concluded deformation in a small chunk of time (3600 epochs) one hour data.