Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/11611
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sakin, A.O. | - |
dc.contributor.author | Tan, H. | - |
dc.contributor.author | Orduyilmaz, A. | - |
dc.date.accessioned | 2024-06-19T14:55:34Z | - |
dc.date.available | 2024-06-19T14:55:34Z | - |
dc.date.issued | 2024 | - |
dc.identifier.isbn | 9783800762873 | - |
dc.identifier.issn | 2197-4403 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/11611 | - |
dc.description | 15th European Conference on Synthetic Aperture Radar, EUSAR 2024 -- 23 April 2024 through 26 April 2024 -- 199491 | en_US |
dc.description.abstract | High-resolution Direction of Arrival estimation is critical in radar-based target detection, particularly with limited snapshots. Our approach utilizes efficient computational techniques for precise 2D-paired-DOA estimation, employing a sparsely arranged V-shaped coprime array for its sensor element efficiency. To enhance reliability under low snapshot conditions, we integrate a Denoising Autoencoder to correct errors from noise and snapshot limitations. Subsequently, the DAE's output is fed into an SS-MUSIC algorithm, yielding an impressive over 80 percent DOA estimation accuracy improvement. This method offers a robust solution for high-resolution DOA estimation in scenarios constrained by limited snapshots. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Computational efficiency | en_US |
dc.subject | Direction of arrival | en_US |
dc.subject | Learning systems | en_US |
dc.subject | Multiple signal classification | en_US |
dc.subject | Radar antennas | en_US |
dc.subject | Tracking radar | en_US |
dc.subject | Auto encoders | en_US |
dc.subject | Computational technique | en_US |
dc.subject | Coprime | en_US |
dc.subject | De-noising | en_US |
dc.subject | Direction of arrival estimation | en_US |
dc.subject | DOA estimation | en_US |
dc.subject | High resolution | en_US |
dc.subject | Limited snapshots | en_US |
dc.subject | Sensor elements | en_US |
dc.subject | Targets detection | en_US |
dc.subject | Antenna arrays | en_US |
dc.title | Denoising Autoencoder-Driven Direction-Of Estimation With V-Shaped Coprime Antenna Array | en_US |
dc.type | Conference Object | en_US |
dc.department | TOBB ETÜ | en_US |
dc.identifier.startpage | 576 | en_US |
dc.identifier.endpage | 581 | en_US |
dc.identifier.scopus | 2-s2.0-85193986238 | en_US |
dc.institutionauthor | Orduyilmaz, A. | - |
dc.authorscopusid | 57771669800 | - |
dc.authorscopusid | 59138650100 | - |
dc.authorscopusid | 23490170000 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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