טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
M.Sc Thesis
M.Sc StudentBoico Lesia
SubjectModeling Tropospheric Delay in GPS Measurements in
Mountainous Areas
DepartmentDepartment of Civil and Environmental Engineering
Supervisor Professor Gilad Even-Tzur
Full Thesis text - in Hebrew Full thesis text - Hebrew Version


Abstract

This research is focus on the influence of tropospheric delay on GPS measurements. In order to examine the tropospheric delay effects, standard atmospheric parameters and meteorological data gathered along with the measurements were used throughout the solution process of tropospheric delay parameters.

The tropospheric delay can be separated into the wet component and the dry component and they are influenced by three atmospheric factors: air pressure, temperature, and humidity percentage. Solving the tropospheric delay parameters for GPS measurements is performed by solving different models. Each model is divided into two components, one to solve the dry component, and the second to solve the wet component.

This study utilizes three common models that used to calculate the tropospheric delay: Saastamoinen, Hopfield and Goad&Goodman. Based on those models the study aims were: (1) Examine and learn the difference between the solutions obtained through the different models using standard atmospheric parameters.(2) Examine and learn the difference between the solutions obtained through the different models using real meteorological data.(3) Examine the influence of meteorological data density on the solution of the tropospheric delay parameters. (4) Examine the influence of missing meteorological data on the solution of the tropospheric delay parameters.

In this study data were gathered in two areas: Carmel ridge and Golan heights. In both networks GPS measurements were collected, meteorological data were gathered only in Carmel ridge.

Examination of the solutions with each models led to conclusion that no fixed trend can be identified in the distinctions between the different models. There is no way of determining the best model for the solution. All models have proven their quality and efficiency for the data that were examined in this research.

This research has presented the differences in the tropospheric delays when using standard atmospheric parameters on the one hand, and when using real meteorological data on the other hand. When using meteorological data, the results obtained were less accurate and the distinctions between the models were bigger than the ones that were obtained with standard atmospheric parameters. The results had shown that using meteorological data is harming the results. Even though, it cannot be assumed that meteorological data should not be used for the solution, but that the models are not suited for meteorological data.