A feasibility study into total electron content prediction using neural networks
- Authors: Habarulema, John Bosco
- Date: 2008
- Subjects: Electrons , Neural networks (Computer science) , Global Positioning System , Ionosphere , Ionospheric electron density
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5466 , http://hdl.handle.net/10962/d1005251 , Electrons , Neural networks (Computer science) , Global Positioning System , Ionosphere , Ionospheric electron density
- Description: Global Positioning System (GPS) networks provide an opportunity to study the dynamics and continuous changes in the ionosphere by supplementing ionospheric measurements which are usually obtained by various techniques such as ionosondes, incoherent scatter radars and satellites. Total electron content (TEC) is one of the physical quantities that can be derived from GPS data, and provides an indication of ionospheric variability. This thesis presents a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC. The South African GPS receiver network is operated and maintained by the Chief Directorate Surveys and Mapping (CDSM) in Cape Town, South Africa. Three South African locations were identified and used in the development of an input space and NN architecture for the model. The input space includes the day number (seasonal variation), hour (diurnal variation), sunspot number (measure of the solar activity), and magnetic index(measure of the magnetic activity). An attempt to study the effects of solar wind on TEC variability was carried out using the Advanced Composition Explorer (ACE) data and it is recommended that more study be done using low altitude satellite data. An analysis was done by comparing predicted NN TEC with TEC values from the IRI2001 version of the International Reference Ionosphere (IRI), validating GPS TEC with ionosonde TEC (ITEC) and assessing the performance of the NN model during equinoxes and solstices. Results show that NNs predict GPS TEC more accurately than the IRI at South African GPS locations, but that more good quality GPS data is required before a truly representative empirical GPS TEC model can be released.
- Full Text:
- Authors: Habarulema, John Bosco
- Date: 2008
- Subjects: Electrons , Neural networks (Computer science) , Global Positioning System , Ionosphere , Ionospheric electron density
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5466 , http://hdl.handle.net/10962/d1005251 , Electrons , Neural networks (Computer science) , Global Positioning System , Ionosphere , Ionospheric electron density
- Description: Global Positioning System (GPS) networks provide an opportunity to study the dynamics and continuous changes in the ionosphere by supplementing ionospheric measurements which are usually obtained by various techniques such as ionosondes, incoherent scatter radars and satellites. Total electron content (TEC) is one of the physical quantities that can be derived from GPS data, and provides an indication of ionospheric variability. This thesis presents a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC. The South African GPS receiver network is operated and maintained by the Chief Directorate Surveys and Mapping (CDSM) in Cape Town, South Africa. Three South African locations were identified and used in the development of an input space and NN architecture for the model. The input space includes the day number (seasonal variation), hour (diurnal variation), sunspot number (measure of the solar activity), and magnetic index(measure of the magnetic activity). An attempt to study the effects of solar wind on TEC variability was carried out using the Advanced Composition Explorer (ACE) data and it is recommended that more study be done using low altitude satellite data. An analysis was done by comparing predicted NN TEC with TEC values from the IRI2001 version of the International Reference Ionosphere (IRI), validating GPS TEC with ionosonde TEC (ITEC) and assessing the performance of the NN model during equinoxes and solstices. Results show that NNs predict GPS TEC more accurately than the IRI at South African GPS locations, but that more good quality GPS data is required before a truly representative empirical GPS TEC model can be released.
- Full Text:
Ionospheric total electron content variability and its influence in radio astronomy
- Authors: Botai, Ondego Joel
- Date: 2006
- Subjects: Electrons , Global Positioning System , Global Positioning System -- Data processing , Ionosphere , Ionospheric radio wave propagation
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5473 , http://hdl.handle.net/10962/d1005258 , Electrons , Global Positioning System , Global Positioning System -- Data processing , Ionosphere , Ionospheric radio wave propagation
- Description: Ionospheric phase delays of radio signals from Global Positioning System (GPS) satellites have been used to compute ionospheric Total Electron Content (TEC). An extended Chapman profle model is used to estimate the electron density profles and TEC. The Chapman profle that can be used to predict TEC over the mid-latitudes only applies during day time. To model night time TEC variability, a polynomial function is fitted to the night time peak electron density profles derived from the online International Reference Ionosphere (IRI) 2001. The observed and predicted TEC and its variability have been used to study ionospheric in°uence on Radio Astronomy in South Africa region. Di®erential phase delays of the radio signals from Radio Astronomy sources have been simulated using TEC. Using the simulated phase delays, the azimuth and declination o®sets of the radio sources have been estimated. Results indicate that, pointing errors of the order of miliarcseconds (mas) are likely if the ionospheric phase delays are not corrected for. These delays are not uniform and vary over a broad spectrum of timescales. This implies that fast frequency (referencing) switching, closure phases and fringe ¯tting schemes for ionospheric correction in astrometry are not the best option as they do not capture the real state of the ionosphere especially if the switching time is greater than the ionospheric TEC variability. However, advantage can be taken of the GPS satellite data available at intervals of a second from the GPS receiver network in South Africa to derive parameters which could be used to correct for the ionospheric delays. Furthermore GPS data can also be used to monitor the occurrence of scintillations, (which might corrupt radio signals) especially for the proposed, Square Kilometer Array (SKA) stations closer to the equatorial belt during magnetic storms and sub-storms. A 10 minute snapshot of GPS data recorded with the Hermanus [34:420 S, 19:220 E ] dual frequency receiver on 2003-04-11 did not show the occurrence of scintillations. This time scale is however too short and cannot be representative. Longer time scales; hours, days, seasons are needed to monitor the occurrence of scintillations.
- Full Text:
- Authors: Botai, Ondego Joel
- Date: 2006
- Subjects: Electrons , Global Positioning System , Global Positioning System -- Data processing , Ionosphere , Ionospheric radio wave propagation
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5473 , http://hdl.handle.net/10962/d1005258 , Electrons , Global Positioning System , Global Positioning System -- Data processing , Ionosphere , Ionospheric radio wave propagation
- Description: Ionospheric phase delays of radio signals from Global Positioning System (GPS) satellites have been used to compute ionospheric Total Electron Content (TEC). An extended Chapman profle model is used to estimate the electron density profles and TEC. The Chapman profle that can be used to predict TEC over the mid-latitudes only applies during day time. To model night time TEC variability, a polynomial function is fitted to the night time peak electron density profles derived from the online International Reference Ionosphere (IRI) 2001. The observed and predicted TEC and its variability have been used to study ionospheric in°uence on Radio Astronomy in South Africa region. Di®erential phase delays of the radio signals from Radio Astronomy sources have been simulated using TEC. Using the simulated phase delays, the azimuth and declination o®sets of the radio sources have been estimated. Results indicate that, pointing errors of the order of miliarcseconds (mas) are likely if the ionospheric phase delays are not corrected for. These delays are not uniform and vary over a broad spectrum of timescales. This implies that fast frequency (referencing) switching, closure phases and fringe ¯tting schemes for ionospheric correction in astrometry are not the best option as they do not capture the real state of the ionosphere especially if the switching time is greater than the ionospheric TEC variability. However, advantage can be taken of the GPS satellite data available at intervals of a second from the GPS receiver network in South Africa to derive parameters which could be used to correct for the ionospheric delays. Furthermore GPS data can also be used to monitor the occurrence of scintillations, (which might corrupt radio signals) especially for the proposed, Square Kilometer Array (SKA) stations closer to the equatorial belt during magnetic storms and sub-storms. A 10 minute snapshot of GPS data recorded with the Hermanus [34:420 S, 19:220 E ] dual frequency receiver on 2003-04-11 did not show the occurrence of scintillations. This time scale is however too short and cannot be representative. Longer time scales; hours, days, seasons are needed to monitor the occurrence of scintillations.
- Full Text:
- «
- ‹
- 1
- ›
- »