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The effect of the Earth’s ionosphere represents the single largest contribution to the Global Navigation Satellite System (GNSS) error budget and abnormal ionospheric conditions can impose serious degradation on GNSS system functionality, including integrity, accuracy and availability. With the growing reliance on GNSS for many modern life applications, actionable ionospheric forecasts can contribute to the understanding and mitigation of the impact of the ionosphere on our technology based society. In this context, the Ionosphere Prediction Service (IPS) project was set up to design and develop a prototype platform to translate the forecast of the ionospheric effects into a service customized for specific GNSS user communities. To achieve this overarching aim, four different product groups dealing with solar activity, ionospheric activity, GNSS receiver performance and service performance have been developed and integrated into a service chain, which is made available through a web based platform. This paper provides an overview of the IPS project describing its overall architecture, products and web based platform., Peer Reviewed, Postprint (published version)

GPS and GLONASS are currently the Global Navigation Satellite Systems (GNSS) with full 16 operational capacity. The integration of GPS, GLONASS and future GNSS constellations can 17 provide better accuracy and more reliability in geodetic positioning, in particular for kinematic 18 Precise Point Positioning (PPP), where the satellite geometry is considered a limiting factor to 19 achieve centimeter accuracy. The satellite geometry can change suddenly in kinematic 20 positioning in urban areas or under conditions of strong atmospheric effects such as for instance 21 ionospheric scintillation that may degrade satellite signal quality, causing cycle slips and even 22 loss of lock. Scintillation is caused by small scale irregularities in the ionosphere and is 23 characterized by rapid changes in amplitude and phase of the signal, which are more severe in 24 equatorial and high latitudes geomagnetic regions. In this work, geodetic positioning through the 25 PPP method was evaluated with integrated GPS and GLONASS data collected in the equatorial 26 region under varied scintillation conditions. The GNSS data were processed in kinematic PPP 27 mode and the analyses show accuracy improvements of up to 60% under conditions of strong 28 scintillation when using multi-constellation data instead of GPS data alone. The concepts and 29 analyses related to the ionospheric scintillation effects, the mathematical model involved in PPP 30 with GPS and GLONASS data integration as well as accuracy assessment with data collected 31 under ionospheric scintillation effects are presented.

In ionospheric modeling, the differential code biases (DCBs) are a non-negligible error source, which are routinely estimated by the different analysis centers of the International GNSS Service (IGS) as a by-product of their global ionospheric analysis. These are, however, estimated only for the IGS station receivers and for all the satellites of the different GNSS constellations. A technique is proposed for estimating the receiver and satellites DCBs in a global or regional network by first estimating the DCB of one receiver set as reference. This receiver DCB is then used as a ‘known’ parameter to constrain the global ionospheric solution, where the receiver and satellite DCBs are estimated for the entire network. This is in contrast to the constraint used by the IGS, which assumes that the involved satellites DCBs have a zero mean. The ‘known’ receiver DCB is obtained by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. When applying the proposed technique for Global Positioning System legacy signals, mean offsets in the order of 3 ns for satellites and receivers were found to exist between the estimated DCBs and the IGS published DCBs. It was shown that these estimated DCBs are fairly stable in time, especially for the legacy signals. When the proposed technique is applied for the DCBs estimation using the newer Galileo signals, an agreement at the level of 1–2 ns was found between the estimated DCBs and the manufacturer’s measured DCBs, as published by the European Space Agency, for the three still operational Galileo in-orbit validation satellites.

Ionospheric conditions at low latitudes are extremely harsh due to the frequent occurrence of scintillation and the presence of strong TEC gradients. For this study, the São Paulo state region in Brazil is chosen as a test area. This study presents a strategy to mitigate the ionospheric impact on RTK positioning with an experimental result. The proposed strategy explores two approaches that can be applied simultaneously: a) to mitigate the scintillation effect on the GNSS signals by refining the stochastic model of the corresponding observations and b) to precisely estimate the residual double difference ionospheric delay by exploiting an accurate TEC map. The strategy was tested on a long baseline kinematic processing under strong scintillation conditions (DOY21 in 2014). Significant improvements were observed when the combined use of the two mitigation approaches described above was compared with the use of conventional state-of-the-art approaches.

GPS and GLONASS are currently the Global Navigation Satellite Systems (GNSS) with full 16 operational capacity. The integration of GPS, GLONASS and future GNSS constellations can 17 provide better accuracy and more reliability in geodetic positioning, in particular for kinematic 18 Precise Point Positioning (PPP), where the satellite geometry is considered a limiting factor to 19 achieve centimeter accuracy. The satellite geometry can change suddenly in kinematic 20 positioning in urban areas or under conditions of strong atmospheric effects such as for instance 21 ionospheric scintillation that may degrade satellite signal quality, causing cycle slips and even 22 loss of lock. Scintillation is caused by small scale irregularities in the ionosphere and is 23 characterized by rapid changes in amplitude and phase of the signal, which are more severe in 24 equatorial and high latitudes geomagnetic regions. In this work, geodetic positioning through the 25 PPP method was evaluated with integrated GPS and GLONASS data collected in the equatorial 26 region under varied scintillation conditions. The GNSS data were processed in kinematic PPP 27 mode and the analyses show accuracy improvements of up to 60% under conditions of strong 28 scintillation when using multi-constellation data instead of GPS data alone. The concepts and 29 analyses related to the ionospheric scintillation effects, the mathematical model involved in PPP 30 with GPS and GLONASS data integration as well as accuracy assessment with data collected 31 under ionospheric scintillation effects are presented.

In ionospheric modeling, the differential code biases (DCBs) are a non-negligible error source, which are routinely estimated by the different analysis centers of the International GNSS Service (IGS) as a by-product of their global ionospheric analysis. These are, however, estimated only for the IGS station receivers and for all the satellites of the different GNSS constellations. A technique is proposed for estimating the receiver and satellites DCBs in a global or regional network by first estimating the DCB of one receiver set as reference. This receiver DCB is then used as a ‘known’ parameter to constrain the global ionospheric solution, where the receiver and satellite DCBs are estimated for the entire network. This is in contrast to the constraint used by the IGS, which assumes that the involved satellites DCBs have a zero mean. The ‘known’ receiver DCB is obtained by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. When applying the proposed technique for Global Positioning System legacy signals, mean offsets in the order of 3 ns for satellites and receivers were found to exist between the estimated DCBs and the IGS published DCBs. It was shown that these estimated DCBs are fairly stable in time, especially for the legacy signals. When the proposed technique is applied for the DCBs estimation using the newer Galileo signals, an agreement at the level of 1–2 ns was found between the estimated DCBs and the manufacturer’s measured DCBs, as published by the European Space Agency, for the three still operational Galileo in-orbit validation satellites.

Ionospheric conditions at low latitudes are extremely harsh due to the frequent occurrence of scintillation and the presence of strong TEC gradients. For this study, the São Paulo state region in Brazil is chosen as a test area. This study presents a strategy to mitigate the ionospheric impact on RTK positioning with an experimental result. The proposed strategy explores two approaches that can be applied simultaneously: a) to mitigate the scintillation effect on the GNSS signals by refining the stochastic model of the corresponding observations and b) to precisely estimate the residual double difference ionospheric delay by exploiting an accurate TEC map. The strategy was tested on a long baseline kinematic processing under strong scintillation conditions (DOY21 in 2014). Significant improvements were observed when the combined use of the two mitigation approaches described above was compared with the use of conventional state-of-the-art approaches.

In ionospheric modeling, the differential code biases (DCBs) are a non-negligible error source, which are routinely estimated by the different analysis centers of the International GNSS Service (IGS) as a by-product of their global ionospheric analysis. These are, however, estimated only for the IGS station receivers and for all the satellites of the different GNSS constellations. A technique is proposed for estimating the receiver and satellites DCBs in a global or regional network by first estimating the DCB of one receiver set as reference. This receiver DCB is then used as a ‘known’ parameter to constrain the global ionospheric solution, where the receiver and satellite DCBs are estimated for the entire network. This is in contrast to the constraint used by the IGS, which assumes that the involved satellites DCBs have a zero mean. The ‘known’ receiver DCB is obtained by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. When applying the proposed technique for Global Positioning System legacy signals, mean offsets in the order of 3 ns for satellites and receivers were found to exist between the estimated DCBs and the IGS published DCBs. It was shown that these estimated DCBs are fairly stable in time, especially for the legacy signals. When the proposed technique is applied for the DCBs estimation using the newer Galileo signals, an agreement at the level of 1–2 ns was found between the estimated DCBs and the manufacturer’s measured DCBs, as published by the European Space Agency, for the three still operational Galileo in-orbit validation satellites.

GPS and GLONASS are currently the Global Navigation Satellite Systems (GNSS) with full 16 operational capacity. The integration of GPS, GLONASS and future GNSS constellations can 17 provide better accuracy and more reliability in geodetic positioning, in particular for kinematic 18 Precise Point Positioning (PPP), where the satellite geometry is considered a limiting factor to 19 achieve centimeter accuracy. The satellite geometry can change suddenly in kinematic 20 positioning in urban areas or under conditions of strong atmospheric effects such as for instance 21 ionospheric scintillation that may degrade satellite signal quality, causing cycle slips and even 22 loss of lock. Scintillation is caused by small scale irregularities in the ionosphere and is 23 characterized by rapid changes in amplitude and phase of the signal, which are more severe in 24 equatorial and high latitudes geomagnetic regions. In this work, geodetic positioning through the 25 PPP method was evaluated with integrated GPS and GLONASS data collected in the equatorial 26 region under varied scintillation conditions. The GNSS data were processed in kinematic PPP 27 mode and the analyses show accuracy improvements of up to 60% under conditions of strong 28 scintillation when using multi-constellation data instead of GPS data alone. The concepts and 29 analyses related to the ionospheric scintillation effects, the mathematical model involved in PPP 30 with GPS and GLONASS data integration as well as accuracy assessment with data collected 31 under ionospheric scintillation effects are presented.

Ionospheric conditions at low latitudes are extremely harsh due to the frequent occurrence of scintillation and the presence of strong TEC gradients. For this study, the São Paulo state region in Brazil is chosen as a test area. This study presents a strategy to mitigate the ionospheric impact on RTK positioning with an experimental result. The proposed strategy explores two approaches that can be applied simultaneously: a) to mitigate the scintillation effect on the GNSS signals by refining the stochastic model of the corresponding observations and b) to precisely estimate the residual double difference ionospheric delay by exploiting an accurate TEC map. The strategy was tested on a long baseline kinematic processing under strong scintillation conditions (DOY21 in 2014). Significant improvements were observed when the combined use of the two mitigation approaches described above was compared with the use of conventional state-of-the-art approaches.

GPS and GLONASS are currently the Global Navigation Satellite Systems (GNSS) with full 16 operational capacity. The integration of GPS, GLONASS and future GNSS constellations can 17 provide better accuracy and more reliability in geodetic positioning, in particular for kinematic 18 Precise Point Positioning (PPP), where the satellite geometry is considered a limiting factor to 19 achieve centimeter accuracy. The satellite geometry can change suddenly in kinematic 20 positioning in urban areas or under conditions of strong atmospheric effects such as for instance 21 ionospheric scintillation that may degrade satellite signal quality, causing cycle slips and even 22 loss of lock. Scintillation is caused by small scale irregularities in the ionosphere and is 23 characterized by rapid changes in amplitude and phase of the signal, which are more severe in 24 equatorial and high latitudes geomagnetic regions. In this work, geodetic positioning through the 25 PPP method was evaluated with integrated GPS and GLONASS data collected in the equatorial 26 region under varied scintillation conditions. The GNSS data were processed in kinematic PPP 27 mode and the analyses show accuracy improvements of up to 60% under conditions of strong 28 scintillation when using multi-constellation data instead of GPS data alone. The concepts and 29 analyses related to the ionospheric scintillation effects, the mathematical model involved in PPP 30 with GPS and GLONASS data integration as well as accuracy assessment with data collected 31 under ionospheric scintillation effects are presented.

In ionospheric modeling, the differential code biases (DCBs) are a non-negligible error source, which are routinely estimated by the different analysis centers of the International GNSS Service (IGS) as a by-product of their global ionospheric analysis. These are, however, estimated only for the IGS station receivers and for all the satellites of the different GNSS constellations. A technique is proposed for estimating the receiver and satellites DCBs in a global or regional network by first estimating the DCB of one receiver set as reference. This receiver DCB is then used as a ‘known’ parameter to constrain the global ionospheric solution, where the receiver and satellite DCBs are estimated for the entire network. This is in contrast to the constraint used by the IGS, which assumes that the involved satellites DCBs have a zero mean. The ‘known’ receiver DCB is obtained by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. When applying the proposed technique for Global Positioning System legacy signals, mean offsets in the order of 3 ns for satellites and receivers were found to exist between the estimated DCBs and the IGS published DCBs. It was shown that these estimated DCBs are fairly stable in time, especially for the legacy signals. When the proposed technique is applied for the DCBs estimation using the newer Galileo signals, an agreement at the level of 1–2 ns was found between the estimated DCBs and the manufacturer’s measured DCBs, as published by the European Space Agency, for the three still operational Galileo in-orbit validation satellites.

Ionospheric conditions at low latitudes are extremely harsh due to the frequent occurrence of scintillation and the presence of strong TEC gradients. For this study, the São Paulo state region in Brazil is chosen as a test area. This study presents a strategy to mitigate the ionospheric impact on RTK positioning with an experimental result. The proposed strategy explores two approaches that can be applied simultaneously: a) to mitigate the scintillation effect on the GNSS signals by refining the stochastic model of the corresponding observations and b) to precisely estimate the residual double difference ionospheric delay by exploiting an accurate TEC map. The strategy was tested on a long baseline kinematic processing under strong scintillation conditions (DOY21 in 2014). Significant improvements were observed when the combined use of the two mitigation approaches described above was compared with the use of conventional state-of-the-art approaches.

GPS and GLONASS are currently the Global Navigation Satellite Systems (GNSS) with full 16 operational capacity. The integration of GPS, GLONASS and future GNSS constellations can 17 provide better accuracy and more reliability in geodetic positioning, in particular for kinematic 18 Precise Point Positioning (PPP), where the satellite geometry is considered a limiting factor to 19 achieve centimeter accuracy. The satellite geometry can change suddenly in kinematic 20 positioning in urban areas or under conditions of strong atmospheric effects such as for instance 21 ionospheric scintillation that may degrade satellite signal quality, causing cycle slips and even 22 loss of lock. Scintillation is caused by small scale irregularities in the ionosphere and is 23 characterized by rapid changes in amplitude and phase of the signal, which are more severe in 24 equatorial and high latitudes geomagnetic regions. In this work, geodetic positioning through the 25 PPP method was evaluated with integrated GPS and GLONASS data collected in the equatorial 26 region under varied scintillation conditions. The GNSS data were processed in kinematic PPP 27 mode and the analyses show accuracy improvements of up to 60% under conditions of strong 28 scintillation when using multi-constellation data instead of GPS data alone. The concepts and 29 analyses related to the ionospheric scintillation effects, the mathematical model involved in PPP 30 with GPS and GLONASS data integration as well as accuracy assessment with data collected 31 under ionospheric scintillation effects are presented.

In ionospheric modeling, the differential code biases (DCBs) are a non-negligible error source, which are routinely estimated by the different analysis centers of the International GNSS Service (IGS) as a by-product of their global ionospheric analysis. These are, however, estimated only for the IGS station receivers and for all the satellites of the different GNSS constellations. A technique is proposed for estimating the receiver and satellites DCBs in a global or regional network by first estimating the DCB of one receiver set as reference. This receiver DCB is then used as a ‘known’ parameter to constrain the global ionospheric solution, where the receiver and satellite DCBs are estimated for the entire network. This is in contrast to the constraint used by the IGS, which assumes that the involved satellites DCBs have a zero mean. The ‘known’ receiver DCB is obtained by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. When applying the proposed technique for Global Positioning System legacy signals, mean offsets in the order of 3 ns for satellites and receivers were found to exist between the estimated DCBs and the IGS published DCBs. It was shown that these estimated DCBs are fairly stable in time, especially for the legacy signals. When the proposed technique is applied for the DCBs estimation using the newer Galileo signals, an agreement at the level of 1–2 ns was found between the estimated DCBs and the manufacturer’s measured DCBs, as published by the European Space Agency, for the three still operational Galileo in-orbit validation satellites.

Ionospheric conditions at low latitudes are extremely harsh due to the frequent occurrence of scintillation and the presence of strong TEC gradients. For this study, the São Paulo state region in Brazil is chosen as a test area. This study presents a strategy to mitigate the ionospheric impact on RTK positioning with an experimental result. The proposed strategy explores two approaches that can be applied simultaneously: a) to mitigate the scintillation effect on the GNSS signals by refining the stochastic model of the corresponding observations and b) to precisely estimate the residual double difference ionospheric delay by exploiting an accurate TEC map. The strategy was tested on a long baseline kinematic processing under strong scintillation conditions (DOY21 in 2014). Significant improvements were observed when the combined use of the two mitigation approaches described above was compared with the use of conventional state-of-the-art approaches.