Martin del Campo Becerra, Gustavo Daniel und Torres García, Eduardo und Serafín García, Sergio Alejandro und Torres Román, Deni Librado und Reigber, Andreas (2022) REGULARIZATION PARAMETER SELECTION FOR TOMOSAR IMAGING WITH SINGLE AND DUAL POLARIMETRIC OBSERVATIONS. In: 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, Seiten 68-71. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2022-07-17 - 2022-07-22, Kuala Lumpur, Malaysia. doi: 10.1109/IGARSS46834.2022.9884893. ISBN 978-166542792-0. ISSN 2153-7003.
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Offizielle URL: https://ieeexplore.ieee.org/document/9884893
Kurzfassung
Polarimetric focusing techniques for synthetic aperture radar (SAR) tomography (TomoSAR) pursue finding optimal polarization combinations to extract the associated scattering mechanisms and height of reflectors. Regularization approaches like weighted covariance fitting (WCF), implemented in an iterative manner, attain finer resolution than conventional focusing techniques (e.g., Capon). Such approaches normally entail the selection of a regularization parameter and a first estimate of the power spectrum pattern. Regularization parameter selection via L-Curve method requires providing the scattering vector; nonetheless, it may not be always available, especially when not working at full resolution. Manipulations previously done to the data covariance matrix (e.g., pre-summing) must be equivalent in the scattering vector, which may not be at all times feasible. Accordingly, this article suggests modifying the L-Curve method to work exclusively with data covariance matrices. The proposed novel strategy is applied to WCF, considering single and dual channels. Iterations are stopped based on the Akaike information criterion.
elib-URL des Eintrags: | https://elib.dlr.de/186871/ | ||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||
Titel: | REGULARIZATION PARAMETER SELECTION FOR TOMOSAR IMAGING WITH SINGLE AND DUAL POLARIMETRIC OBSERVATIONS | ||||||||||||||||||||||||
Autoren: |
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Datum: | Juli 2022 | ||||||||||||||||||||||||
Erschienen in: | 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 | ||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||||||
DOI: | 10.1109/IGARSS46834.2022.9884893 | ||||||||||||||||||||||||
Seitenbereich: | Seiten 68-71 | ||||||||||||||||||||||||
ISSN: | 2153-7003 | ||||||||||||||||||||||||
ISBN: | 978-166542792-0 | ||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||
Stichwörter: | L-Curve, synthetic aperture radar (SAR), tomography, weighted covariance fitting (WCF). | ||||||||||||||||||||||||
Veranstaltungstitel: | IEEE International Geoscience and Remote Sensing Symposium (IGARSS) | ||||||||||||||||||||||||
Veranstaltungsort: | Kuala Lumpur, Malaysia | ||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||
Veranstaltungsbeginn: | 17 Juli 2022 | ||||||||||||||||||||||||
Veranstaltungsende: | 22 Juli 2022 | ||||||||||||||||||||||||
Veranstalter : | IEEE GRSS | ||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Flugzeug-SAR | ||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Hochfrequenztechnik und Radarsysteme > SAR-Technologie | ||||||||||||||||||||||||
Hinterlegt von: | Martin del Campo Becerra, Gustavo | ||||||||||||||||||||||||
Hinterlegt am: | 15 Jun 2022 15:01 | ||||||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:48 |
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