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Software Infrastructure for NeXtRAD Development in Julia Programming Language
This dissertation presents the implementation of signal processing infrastructure in Julia Programming Language. The aim is to aid sea clutter analysis using NetRAD and NeXtRAD data. Scripts written in Julia Programming Language and supporting documentation on how to navigate through compressed HDF5...
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| Format: | Thesis |
| Language: | English |
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Department of Electrical Engineering
2017
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| _version_ | 1867613191255621632 |
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| access_status_str | Open Access |
| author | Jonkers, Stephanie Cavale |
| author2 | O'Hagan, Daniel W |
| author_browse | Jonkers, Stephanie Cavale O'Hagan, Daniel W |
| author_facet | O'Hagan, Daniel W Jonkers, Stephanie Cavale |
| author_sort | Jonkers, Stephanie Cavale |
| collection | Thesis |
| description | This dissertation presents the implementation of signal processing infrastructure in Julia Programming Language. The aim is to aid sea clutter analysis using NetRAD and NeXtRAD data. Scripts written in Julia Programming Language and supporting documentation on how to navigate through compressed HDF5 files, apply pulse compression, pulse-Doppler processing and an adaptive LMS filter for interference suppression is presented. Both serial and multi-core pulse compression and pulse-Doppler processing functions are implemented. The assessment of the algorithm computation times highlights Julia's dependence on large amounts of RAM and slow data movement between worker processes. Multi-core pulse compression on 130 000 pulses each with 2 048 samples was not found to be faster than the serial implementation. Multi-core pulse-Doppler processing was able to achieve a speedup of 1:6 for a dataset with 102 400 pulses. Datasets larger than 102 400 pulses resulted in a memory bottleneck. The adaptive LMS filter was validated by applying an OS-CFAR detector to match filtered data before and after filtering. The filter was unable to improve the precision or recall for highly cluttered pulses, but was able to reduce the number of highly cluttered pulses. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/22995 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:13.078Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/22995 Software Infrastructure for NeXtRAD Development in Julia Programming Language Jonkers, Stephanie Cavale O'Hagan, Daniel W Electrical Engineering This dissertation presents the implementation of signal processing infrastructure in Julia Programming Language. The aim is to aid sea clutter analysis using NetRAD and NeXtRAD data. Scripts written in Julia Programming Language and supporting documentation on how to navigate through compressed HDF5 files, apply pulse compression, pulse-Doppler processing and an adaptive LMS filter for interference suppression is presented. Both serial and multi-core pulse compression and pulse-Doppler processing functions are implemented. The assessment of the algorithm computation times highlights Julia's dependence on large amounts of RAM and slow data movement between worker processes. Multi-core pulse compression on 130 000 pulses each with 2 048 samples was not found to be faster than the serial implementation. Multi-core pulse-Doppler processing was able to achieve a speedup of 1:6 for a dataset with 102 400 pulses. Datasets larger than 102 400 pulses resulted in a memory bottleneck. The adaptive LMS filter was validated by applying an OS-CFAR detector to match filtered data before and after filtering. The filter was unable to improve the precision or recall for highly cluttered pulses, but was able to reduce the number of highly cluttered pulses. 2017-01-24T11:37:33Z 2017-01-24T11:37:33Z 2016 Master Thesis Masters MSc (Eng) http://hdl.handle.net/11427/22995 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical Engineering Jonkers, Stephanie Cavale Software Infrastructure for NeXtRAD Development in Julia Programming Language |
| thesis_degree_str | Master's |
| title | Software Infrastructure for NeXtRAD Development in Julia Programming Language |
| title_full | Software Infrastructure for NeXtRAD Development in Julia Programming Language |
| title_fullStr | Software Infrastructure for NeXtRAD Development in Julia Programming Language |
| title_full_unstemmed | Software Infrastructure for NeXtRAD Development in Julia Programming Language |
| title_short | Software Infrastructure for NeXtRAD Development in Julia Programming Language |
| title_sort | software infrastructure for nextrad development in julia programming language |
| topic | Electrical Engineering |
| url | http://hdl.handle.net/11427/22995 |
| work_keys_str_mv | AT jonkersstephaniecavale softwareinfrastructurefornextraddevelopmentinjuliaprogramminglanguage |