Verification and Calibration of the ICEBEAR Radar through GPU Acceleration, Noise Characterization and Calculation, and Radio Galaxy Phase Calibration
| dc.contributor.advisor | Hussey, Glenn | |
| dc.contributor.committeeMember | McWilliams, Kathryn | |
| dc.contributor.committeeMember | Steele, Tom | |
| dc.contributor.committeeMember | Butler, Samuel | |
| dc.contributor.committeeMember | Bourassa, Adam | |
| dc.creator | Galeschuk, Draven T.K. | |
| dc.date.accessioned | 2021-06-15T13:28:37Z | |
| dc.date.available | 2021-06-15T13:28:37Z | |
| dc.date.created | 2021-11 | |
| dc.date.issued | 2021-06-15 | |
| dc.date.submitted | November 2021 | |
| dc.date.updated | 2021-06-15T13:28:37Z | |
| dc.description.abstract | The research performed for this thesis focused on verifying, quantifying, calibrating, and improving the Ionospheric Continuous Wave (CW) E-region Bi-static Radar (ICEBEAR) data observations and quality. Graphical processing unit (GPU) acceleration was used to improve the computation speed of ICEBEAR data analysis. The ICEBEAR noise floor was studied to better understand the ICEBEAR noise environment and verify the signal to noise ratio (SNR), which affects all ICEBEAR data products. Finally, a calibration method using the radio galaxy Cygnus~A was developed to enable improved phase calibration of the ICEBEAR receiver antennas. GPUs enable high computational throughput through the use of parallel processing and specific hardware design. This part of my research used the properties of GPUs to accelerate the data analysis of ICEBEAR to be 48 times faster than the original processing capability, enabling real-time analysis of ICEBEAR data. The current noise calculation technique of taking the median power calculation of the ICEBEAR field of view is reasonable, but it is recommended that ICEBEAR switch to using an average of the furthest ranges measured by the radar. The dominant noise sources in the radar changes based on ionospheric activity, where self-clutter dominates during active periods and cosmic noise dominates during quite periods. This impacts the computation of the SNR data product and is better quantified by a far range average for all 45 baselines in the ICEBEAR radar. The detection of Cygnus~A during quiet ionospheric periods was used to calculate phase self-calibrations for the radar by comparing the measured phase difference between antennas to the expected theoretical phase difference of Cygnus~A. The technique is shown to generate similar and complementary results to the current spectrum analyzer calibration technique. Future improvements to ICEBEAR imaging analysis and future research into the improved observation of Cygnus~A will allow this new phase self-calibration method to be actively used for ICEBEAR. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/10388/13427 | |
| dc.subject | ICEBEAR | |
| dc.subject | E-region | |
| dc.subject | space physics | |
| dc.subject | radar | |
| dc.title | Verification and Calibration of the ICEBEAR Radar through GPU Acceleration, Noise Characterization and Calculation, and Radio Galaxy Phase Calibration | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Physics and Engineering Physics | |
| thesis.degree.discipline | Physics | |
| thesis.degree.grantor | University of Saskatchewan | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science (M.Sc.) |