Enhanced Local Ionosphere Model for Multi-Constellations Single Frequency Precise Point Positioning Applications: Egyptian Case Study

Abstract The positioning accuracy of single frequency precise point positioning (SFPPP) attributes mainly to the ionosphere error, which strongly affects GNSS signals. When GNSS signals pass through the various ionosphere layers, they will be bent and their speed will be changed due to dispersive nature of ionosphere. To correct the ionosphere error, it is common to use Klobuchar ionosphere model or Global Ionosphere Maps (GIM). However, Klobuchar can deal with only about 50% of the Ionosphere effect and global Ionosphere maps are often inadequate to describe detailed features of local ionosphere because of limited precision and resolution. In this paper, an enhanced local ionosphere model was developed relying on modeling of measurements from a dense Egyptian permanent tracking GNSS network in order to achieve high precision ionosphere delay correction. The performance of the developed enhanced Egyptian ionosphere model (EIM) was verified through multi-constellations SFPPP accuracy for static and kinematic modes. For static mode, 24 hours multi-constellations datasets collected at three selected stations, Alexandria, Cairo, and Aswan, in Egypt on February 27, 2017, to investigate the performance of the developed local ionospheric model in comparison with the Klobuchar, GIM and ionosphere free models. After session time of half an hour, the results show that the performance of static SFPPP based on the developed Egyptian ionospheric map (EIM) achieved a comparable accuracy WRT using ionosphere free model. While using EIM, achieved an improvements of (38%, 28%, and 42%) and (32%, 10%, and 37%) for accuracy of latitude, longitude, and altitude in comparison with using Klobuchar and GIM models, respectively For kinematic mode, datasets of 2 hours of observations with 1 second sampling rate were logged during vehicular test; the test was carried out on the ring road of the city of Cairo, Egypt, on September 16, 2017. After half an hour of kinematic SFPPP data-processing, the performance of using Egyptian ionospheric map (EIM) for ionosphere delay correction, achieved an improvements of three dimension coordinates of (83%, 47%, and 62%) and (57%, 65%, and 21%) with respect to using Klobuchar model and GIM model, respectively.