A neural network based error correction method for radio occultation electron density retrieval

Simple item page
dc.contributor.authorPham, Viet-Cuong
dc.contributor.authorJuang, Jyh-Ching
dc.date.accessioned2018-11-15T18:13:24Z
dc.date.available2018-11-15T18:13:24Z
dc.date.issued2015-10-19
dc.description.abstractAbel inversion techniques have been widely employed to retrieve electron density profiles (EDPs) from radio occultation (RO) measurements, which are available by observing Global Navigation Satellite System (GNSS) satellites from low-earth-orbit (LEO) satellites. It is well known that the ordinary Abel inversion might introduce errors in the retrieval of EDPs when the spherical symmetry assumption is violated. The error, however, is case-dependent; therefore it is desirable to associate an error index or correction coefficient with respect to each retrieved EDP. Several error indices have been proposed but they only deal with electron density at the F2 peak and suffer from some drawbacks. In this paper we propose an artificial neural network (ANN) based error correction method for EDPs obtained by the ordinary Abel inversion. The ANN is first trained to learn the relationship between vertical total electron content (TEC) measurements and retrieval errors at the F2 peak, 220 km and 110 km altitudes; correction coefficients are then estimated to correct the retrieved EDPs at these three altitudes. Experiments using the NeQuick2 model and real FORMOSAT-3/COSMIC RO geometry show that the proposed method outperforms existing ones. Real incoherent scatter radar (ISR) measurements at the Jicamarca Radio Observatory and the global TEC map provided by the International GNSS Service (IGS) are also used to valid the proposed method.es_ES
dc.description.peer-reviewPor pareses_ES
dc.formatapplication/pdfes_ES
dc.identifier.citationPham, V.-C., & Juang, J.-C. (2015). A neural network based error correction method for radio occultation electron density retrieval.==$Journal of Atmospheric and Solar-Terrestrial Physics, 135,$==77-84. https://doi.org/10.1016/j.jastp.2015.10.013es_ES
dc.identifier.doihttps://doi.org/10.1016/j.jastp.2015.10.013es_ES
dc.identifier.journalJournal of Atmospheric and Solar-Terrestrial Physicses_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12816/3639
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.ispartofurn:issn:1364-6826
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.subjectRadio occultationes_ES
dc.subjectElectron density profilees_ES
dc.subjectAbel inversiones_ES
dc.subjectAsymmetry indexes_ES
dc.subjectArtificial neural networkes_ES
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#1.05.01es_ES
dc.titleA neural network based error correction method for radio occultation electron density retrievales_ES
dc.typeinfo:eu-repo/semantics/articlees_ES

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
IGP-1-1-1-1449090276.pdf
Size:
1.95 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
391 B
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Artículos Científicos