3D electron density estimation in the ionosphere
buir.contributor.author | Arıkan, Orhan | |
buir.contributor.orcid | Arıkan, Orhan|0000-0002-3698-8888 | |
dc.citation.epage | 532 | en_US |
dc.citation.spage | 529 | en_US |
dc.contributor.author | Tuna, Hakan | en_US |
dc.contributor.author | Arıkan, Orhan | en_US |
dc.contributor.author | Arıkan, F. | en_US |
dc.coverage.spatial | Trabzon, Turkey | en_US |
dc.date.accessioned | 2016-02-08T11:52:19Z | |
dc.date.available | 2016-02-08T11:52:19Z | |
dc.date.issued | 2014 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description | Date of Conference: 23-25 April 2014 | en_US |
dc.description | Conference Name: 22nd Signal Processing and Communications Applications Conference, SIU 2014 | en_US |
dc.description.abstract | Ionosphere has ion distribution which is variable in space and time. There have been physical and empirical studies for modeling the ionosphere. International Reference Ionosphere extended to Plasmasphere (IRI-Plas) is the most recent model developed for this purpose. However, IRI-Plas presents a model about the ionosphere and its compliance with the instantaneous state of the ionosphere does not provide the accuracy needed for engineering purposes. One of the important information sources about the instantaneous state of the ionosphere is GPS signals. In this study, constructing the ionosphere which is compatible with both the instantaneous ionosphere measurements and the physical structure of the ionosphere is presented as an optimization problem, and solved by using the particle swarm optimization technique. The ionosphere over Turkey is investigated by using the proposed optimization method and the importance of the instantaneous ionosphere measurements obtained from GPS signals is demonstrated. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T11:52:19Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2014 | en |
dc.identifier.doi | 10.1109/SIU.2014.6830282 | en_US |
dc.identifier.issn | 2165-0608 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/27397 | |
dc.language.iso | Turkish | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/SIU.2014.6830282 | en_US |
dc.source.title | Proceedings of the 22nd Signal Processing and Communications Applications Conference, SIU 2014 | en_US |
dc.subject | 3D electron density estimation | en_US |
dc.subject | Ionosphere | en_US |
dc.subject | Carrier concentration | en_US |
dc.subject | Electron density measurement | en_US |
dc.subject | Ionospheric measurement | en_US |
dc.subject | Magnetosphere | en_US |
dc.subject | Particle swarm optimization (PSO) | en_US |
dc.subject | Signal processing | en_US |
dc.subject | International reference ionospheres | en_US |
dc.subject | IRI-Plas | en_US |
dc.subject | Optimization method | en_US |
dc.subject | Optimization problems | en_US |
dc.subject | Particle swarm optimization technique | en_US |
dc.subject | Physical structures | en_US |
dc.title | 3D electron density estimation in the ionosphere | en_US |
dc.title.alternative | İyonkürede 3 boyutlu elektron yoğunluğu kestirimi | en_US |
dc.type | Conference Paper | en_US |
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