Assessment of mm-wave high resolution inverse SAR imaging both with compact and sparse data
| dc.contributor.author | Iqbal, Muhammad Amjad | |
| dc.contributor.author | Anghel, Andrei | |
| dc.contributor.author | Datcu, Datcu | |
| dc.contributor.author | Ederra Urzainqui, Íñigo | |
| dc.contributor.author | Iriarte Galarregui, Juan Carlos | |
| dc.contributor.department | Ingeniería Eléctrica, Electrónica y de Comunicación | es_ES |
| dc.contributor.department | Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza | eu |
| dc.contributor.department | Institute of Smart Cities - ISC | en |
| dc.date.accessioned | 2024-10-11T09:20:56Z | |
| dc.date.available | 2024-10-11T09:20:56Z | |
| dc.date.issued | 2023 | |
| dc.date.updated | 2024-10-11T09:16:56Z | |
| dc.description.abstract | Inverse synthetic aperture radar (ISAR) provides images of objects that are rotated with respect to the radar. An efficient image-focusing algorithm is required to generate ISAR images from the echoes of the raw data. In this study, a monostatic model was deployed to collect radar backscattering data in the millimeter (mm) wave band (67-110 GHz) using targets with circular, rectangular, and non-canonical shapes. The ISAR experiments were performed to assess the imaging performance of the three methods. The ISAR image reconstruction implemented in the wave-number (¿ - k) domain solves the target reflectivity and allows the target to be close to the radar. This shows that the mm-wave radar can achieve a sufficient resolution in the range and azimuth dimensions. Finally, we compared the results with those of spherical wavefront compensation (SWFC) and back-projection (BP) methods. The efficiencies of the three methods were tested using compressible data with wavelet-decomposition-based sparse measurements. To demonstrate the performance of the given methods, the point spread function (PSF) for the impulse response of the mm-wave wire was computed. There is a trade-off: the ¿ - k domain loses resolution compared to the SWFC and BP methods but can obtain a satisfactory image at a lower computational cost. | en |
| dc.description.sponsorship | This work has been funded by Marie Sklodowska-Curie Actions Innovative Training Networks (MSCA-ITN) under the MENELAOS-NT, GA 860370. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Iqbal, M. A., Anghel, A., Datcu, M., Ederra, I., Iriarte, J. C. (2023). Assessment of mm-wave high resolution inverse SAR imaging both with compact and sparse data. In [IEEE], 20th European Radar Conference, EuRAD 2023 (pp. 266-269). Institute of Electrical and Electronics Engineers. https://doi.org/10.23919/EuRAD58043.2023.10288621. | |
| dc.identifier.doi | 10.23919/EuRAD58043.2023.10288621 | |
| dc.identifier.isbn | 978-2-87487-074-3 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/52192 | |
| dc.language.iso | eng | |
| dc.publisher | IEEE | |
| dc.relation.publisherversion | https://doi.org/10.23919/EuRAD58043.2023.10288621 | |
| dc.rights | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work. | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.subject | 2D-DWD | en |
| dc.subject | CS | en |
| dc.subject | ISAR | en |
| dc.subject | mm-wave | en |
| dc.subject | PSF | en |
| dc.subject | SFWC | en |
| dc.subject | Wave-number | en |
| dc.title | Assessment of mm-wave high resolution inverse SAR imaging both with compact and sparse data | en |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | dbe40f43-15e2-46ee-932e-0d66f246b95d | |
| relation.isAuthorOfPublication | cb750d68-162b-4ddf-8573-6d3ed9cd77fc | |
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