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The GNSS observations suffer from different types of errors that could affect the achieved positioning accuracy based on the receiver type used. Single-frequency receivers are widely used worldwide because of its low cost. The ionospheric delay considers the most challenging error for single-frequency GNSS observations. All satellite navigation systems, except GLONASS, are advising their users to correct for the ionospheric delay using a certain model. Those models’ coefficients are sent to users in the system’s navigation message. These models are different in their accuracy and behavior based on its foundation theory as well as the updating rate of their coefficients. The GPS uses Klobuchar model for mitigating the ionospheric delay. BeiDou system (BDS-2) adopts a slightly modified Klobuchar model that resembles GPS ICA (Ionospheric Correction Algorithm) with eight correction parameters but is formulated in a geographic coordinate system with different coefficients in origin and updating rate. Galileo system uses a different model (NeQuick model). This article investigates the behavior of the three models in correcting the ionospheric delay for three stations at different latitudes during 3 months of different states of ionospheric activity, comparing with International GNSS Service-Global Ionospheric Maps (IGS-GIMs). It is advised from this research’s outputs to use the GPS model for mitigating the ionospheric delay in low-latitude regions during the state of low-and medium-activity ionosphere. It is advised to use the BeiDou model for mitigating the ionospheric delay in mid-latitude regions during different states of ionospheric activity. It is advised to use the Galileo model for mitigating the ionospheric delay in high-latitude regions during different states of ionospheric activity. Also, the Galileo model is recommended for mitigating the ionospheric delay for low-latitude regions during the state of high-activity ionosphere.

Behavior of Broadcast Ionospheric-Delay Models from GPS, Beidou, and Galileo Systems