การหาวิธีที่เหมาะสมสำหรับการแปลงค่าพิกัดจีพีเอสประเทศไทยเข้าสู่กรอบอ้างอิงนานาชาติ ปี ค.ศ. 2005 ด้วยซอฟต์แวร์ GIPSY / พัลลภ พยัคเลิศ = Determination of suitable approach for the mapping of the Thai GPS coordinates into the International Terrestrial Reference Frame 2005 (ITRF2005) using GIPSY software / Punlop Payakleard
The GPS Precise Point Positioning (PPP) technique has been widely used for many high precision positioning applications especially in an establishment of national and region reference frames. Among the GPS PPP software packages, the GIPSY-OASIS II software package is the most popular software package used by many research institutes worldwide. The processing of GPS data with the GIPSY-OASIS II software requires three main steps. The first step is to compute a daily GPS solution for each station and the second step is to combine the 7daily GPS solutions into a weekly averaged solution. The final step is to transform a weekly averaged solution into the latest International Terrestrial Reference Frame (ITRF) coordinate solution and this step generally requires the use of available International GNSS service (IGS) stations to compute for transformation parameters. In order to obtain high precision ITRF coordinate solutions, an investigation on a selection of IGS stations used for mapping the weekly averaged solution onto the ITRF solution is therefore needed. This research aims to investigate an effect of number and distribution of IGS stations used on the final ITRF coordinate solution in Thai region. Two different periods of GPS campaign (before and after the 2004 Sumartra-Andaman Earthquake) measured by the Royal Thai Survey Department (RTSD) are used in this investigation. This research has proposed guidelines on how to select suitable IGS stations for the final transformation step. By varying the number of IGS station from 4 to 30 stations, results indicate that the use of at least 14 IGS stations in the final step can produce reliable and accurate ITRF solutions. In addition, it was found that the selection of well-distributed IGS stations yields better results as compared to the poor-distributed IGS stations.
