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:
- Date Issued: 2008
- 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:
- Date Issued: 2008
Particle precipitation effects on the South African ionosphere
- Authors: Sibanda, Patrick
- Date: 2007
- Subjects: Ionosphere -- South Africa , Precipitation (Chemistry) -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5481 , http://hdl.handle.net/10962/d1005267 , Ionosphere -- South Africa , Precipitation (Chemistry) -- South Africa
- Description: Particle precipitation involves the injection of energetic particles into the ionosphere which could increase the ionisation and conductivity of the upper atmosphere. The goal of this study was to examine the ionospheric response and changes due to particle precipitation in the region over South Africa, using a combination of groundbased and satellite instruments. Particle precipitation events were identified from satellite particle flux measurements of the Defence Meteorological Satellite Program (DMSP). Comprehensive studies were done on the events of 5 April, 2000 and 7 October, 2000. Analysis of the data from the satellite instruments indicates that no particle precipitation was observed over the South African region during these events and that it is unlikely to occur during other such events. To validate the data, methods and tools used in this study, precipitation in the South Atlantic anomaly (SAA) region is used. Satellite ion density measurements revealed that strong density enhancements occurred over the SAA region at satellite altitudes during the precipitation events, but this did not occur in the South African region. The measurements also revealed how the ionisation enhancements in the SAA region correlated with geomagnetic and solar activities. Particle precipitation and convective electric fields are two major magnetospheric energy sources to the upper atmosphere in the auroral and the SAA regions. These increase dramatically during geomagnetic storms and can disturb thermospheric circulation in the atmosphere and alter the rates of production and recombination of the ionised species. Ionosonde observations at Grahamstown, South Africa (33.30S, 26.50E), provided the data to build a picture of the response of the ionosphere over the South African region to particle precipitation during the precipitation events. This analysis showed that, within the confines of the available data, no direct connections between particle precipitation events and disturbances in the ionosphere over this region were revealed.
- Full Text:
- Date Issued: 2007
- Authors: Sibanda, Patrick
- Date: 2007
- Subjects: Ionosphere -- South Africa , Precipitation (Chemistry) -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5481 , http://hdl.handle.net/10962/d1005267 , Ionosphere -- South Africa , Precipitation (Chemistry) -- South Africa
- Description: Particle precipitation involves the injection of energetic particles into the ionosphere which could increase the ionisation and conductivity of the upper atmosphere. The goal of this study was to examine the ionospheric response and changes due to particle precipitation in the region over South Africa, using a combination of groundbased and satellite instruments. Particle precipitation events were identified from satellite particle flux measurements of the Defence Meteorological Satellite Program (DMSP). Comprehensive studies were done on the events of 5 April, 2000 and 7 October, 2000. Analysis of the data from the satellite instruments indicates that no particle precipitation was observed over the South African region during these events and that it is unlikely to occur during other such events. To validate the data, methods and tools used in this study, precipitation in the South Atlantic anomaly (SAA) region is used. Satellite ion density measurements revealed that strong density enhancements occurred over the SAA region at satellite altitudes during the precipitation events, but this did not occur in the South African region. The measurements also revealed how the ionisation enhancements in the SAA region correlated with geomagnetic and solar activities. Particle precipitation and convective electric fields are two major magnetospheric energy sources to the upper atmosphere in the auroral and the SAA regions. These increase dramatically during geomagnetic storms and can disturb thermospheric circulation in the atmosphere and alter the rates of production and recombination of the ionised species. Ionosonde observations at Grahamstown, South Africa (33.30S, 26.50E), provided the data to build a picture of the response of the ionosphere over the South African region to particle precipitation during the precipitation events. This analysis showed that, within the confines of the available data, no direct connections between particle precipitation events and disturbances in the ionosphere over this region were revealed.
- Full Text:
- Date Issued: 2007
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