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An apparent delay is occurred in GPS signal due to both refraction and diffraction caused by the atmosphere. The second region of the atmosphere is the ionosphere. The ionosphere is significantly related to GPS and the refraction it causes in GPS signal is considered one of the main source of errors which must be eliminated to determine accurate positions. GPS receiver networks have been used for monitoring the ionosphere for a long time. The ionospheric delay is the most predominant of all the error sources. This delay is a function of the total electron content (TEC). Because of the dispersive nature of the ionosphere, one can estimate the ionospheric delay using the dual frequency GPS. In the current research our primary goal is applying Precise Point Positioning (PPP) observation for accurate ionosphere error modeling, by estimating Ionosphere delay using carrier phase observations from dual frequency GPS receiver. The proposed algorithm was written using MATLAB and was named VIDE program. The proposed Algorithm depends on the geometry-free carrier-phase observations after detecting cycle slip to estimates the ionospheric delay using a spherical ionospheric shell model, in which the vertical delays are described by means of a zenith delay at the station position and latitudinal and longitudinal gradients. Geometry-free carrier-phase observations were applied to avoid unwanted effects of pseudorange measurements, such as code multipath. The ionospheric estimation in this algorithm is performed by means of sequential least-squares adjustment. Finally, an adaptable user interface MATLAB software are capable of estimating ionosphere delay, ambiguity term and ionosphere gradient accurately.

This study aimed to measure and validate altitudes from existing sources with direct GNSS measurements and airborne lidar data. For this purpose, 12 mountain peaks located in the south part of Polish territory were selected. Measurements were performed using a GNSS receiver using the Real-Time Kinematic (RTK) or static techniques enabling altitude measurements with accuracy of 10 cm. GNSS was treated as the primary data source, as the direct field measurements can determine the highest point on each peak. The obtained results were confronted with historical, internet sources, and official altitude data. Moreover, each altitude was determined using lidar data from an airborne lidar dataset of Poland from the ISOK program and provided by the national agency. Significant discrepancies in data were already detected during the analysis of internet materials and traditional maps, up to a few meters. The differences between measured and internet sources in altitude of mountain peak range from 27 cm to 504 cm. This study has shown the need to re-measure the altitudes of the mountain peaks and determine the highest point correctly.

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