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
Verification of Ionospheric tomography using MIDAS over Grahamstown, South Africa
- Authors: Katamzi, Zama Thobeka
- Date: 2008
- Subjects: Ionosphere -- Remote sensing -- South Africa , Atmosphere, Upper , Tomography -- Scientific applications -- South Africa , Global Positioning System
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5497 , http://hdl.handle.net/10962/d1005283 , Ionosphere -- Remote sensing -- South Africa , Atmosphere, Upper , Tomography -- Scientific applications -- South Africa , Global Positioning System
- Description: Global Positioning System (GPS) satellites and receivers are used to derive total electron content (TEC) from the time delay and phase advance of the radiowaves as they travels through the ionosphere. TEC is defined as the integralof the electron density along the satellite-receiver signal path. Electron densityprofiles can be determined from these TEC values using ionospheric tomographic inversion techniques such as Multi-Instrument Data Analysis System (MIDAS).This thesis reports on a study aimed at evaluating the suitability of ionospheric tomography as a tool to derive one-dimensional electron density profiles, using the MIDAS inversion algorithm over Grahamstown, South Africa (33.30◦S, 26.50◦E). The evaluation was done by using ionosonde data from the Louisvale (28.50◦S, 21.20◦E) and Madimbo (22.40◦S, 30.90◦E) stations to create empirical orthonormal functions (EOFs). These EOFs were used by MIDAS in the inversion process to describe the vertical variation of the electron density. Profiles derived from the MIDAS algorithm were compared with profiles obtained from the international Reference Ionosphere (IRI) 2001 model and with ionosonde profiles from the Grahamstown ionosonde station. The optimised MIDAS profiles show a good agreement with the Grahamstown ionosonde profiles. The South African Bottomside Ionospheric Model (SABIM) was used to set the limits within which MIDAS was producing accurate peak electron density (NmF2) values and to define accuracy in this project, with the understanding that the national model (SABIM) is currently the best model for the Grahamstown region. Analysis show that MIDAS produces accurate results during the winter season, which had the lowest root mean square (rms) error of 0.37×1011[e/m3] and an approximately 86% chance of producing NmF2 closer to the actual NmF2 value than the national model SABIM. MIDAS was found to also produce accurate NmF2 values at 12h00 UT, where an approximately 88% chance of producing an accurate NmF2 value, which may deviate from the measured value by 0.72×1011[e/m3], was determined. In conclusion, ionospheric tomographic inversion techniques show promise in the reconstruction of electron density profiles over South Africa, and are worth pursuing further in the future.
- Full Text:
- Date Issued: 2008
- Authors: Katamzi, Zama Thobeka
- Date: 2008
- Subjects: Ionosphere -- Remote sensing -- South Africa , Atmosphere, Upper , Tomography -- Scientific applications -- South Africa , Global Positioning System
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5497 , http://hdl.handle.net/10962/d1005283 , Ionosphere -- Remote sensing -- South Africa , Atmosphere, Upper , Tomography -- Scientific applications -- South Africa , Global Positioning System
- Description: Global Positioning System (GPS) satellites and receivers are used to derive total electron content (TEC) from the time delay and phase advance of the radiowaves as they travels through the ionosphere. TEC is defined as the integralof the electron density along the satellite-receiver signal path. Electron densityprofiles can be determined from these TEC values using ionospheric tomographic inversion techniques such as Multi-Instrument Data Analysis System (MIDAS).This thesis reports on a study aimed at evaluating the suitability of ionospheric tomography as a tool to derive one-dimensional electron density profiles, using the MIDAS inversion algorithm over Grahamstown, South Africa (33.30◦S, 26.50◦E). The evaluation was done by using ionosonde data from the Louisvale (28.50◦S, 21.20◦E) and Madimbo (22.40◦S, 30.90◦E) stations to create empirical orthonormal functions (EOFs). These EOFs were used by MIDAS in the inversion process to describe the vertical variation of the electron density. Profiles derived from the MIDAS algorithm were compared with profiles obtained from the international Reference Ionosphere (IRI) 2001 model and with ionosonde profiles from the Grahamstown ionosonde station. The optimised MIDAS profiles show a good agreement with the Grahamstown ionosonde profiles. The South African Bottomside Ionospheric Model (SABIM) was used to set the limits within which MIDAS was producing accurate peak electron density (NmF2) values and to define accuracy in this project, with the understanding that the national model (SABIM) is currently the best model for the Grahamstown region. Analysis show that MIDAS produces accurate results during the winter season, which had the lowest root mean square (rms) error of 0.37×1011[e/m3] and an approximately 86% chance of producing NmF2 closer to the actual NmF2 value than the national model SABIM. MIDAS was found to also produce accurate NmF2 values at 12h00 UT, where an approximately 88% chance of producing an accurate NmF2 value, which may deviate from the measured value by 0.72×1011[e/m3], was determined. In conclusion, ionospheric tomographic inversion techniques show promise in the reconstruction of electron density profiles over South Africa, and are worth pursuing further in the future.
- Full Text:
- Date Issued: 2008
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