Shi, Yilei und Bamler, Richard und Wang, Yuanyuan und Zhu, Xiao Xiang (2020) Generation of Large-Scale High Quality 3-D Urban Models. In: 2020 IEEE Radar Conference, RadarConf 2020, Seiten 1-6. 2020 IEEE Radar Conference, 2020-09-21 - 2020-09-25, virtual. doi: 10.1109/RadarConf2043947.2020.9266314. ISBN 978-172818942-0. ISSN 1097-5659.
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Offizielle URL: https://ieeexplore.ieee.org/document/9266314
Kurzfassung
Interferometric synthetic aperture radar (InSAR) techniques are powerful tool for reconstructing the 3-D position of scatterers, especially for the urban areas. Since the estimation accuracy depends on the inverse of number of interferograms and signal-to-noise ratio (SNR), it is necessary to use as many as possible interferograms in order to achieve more accurate result. However, the number of interferograms of TanDEM-X data is generally limited for most areas. Therefore, in order to maintain the estimation accuracy, one feasible way is to increase the SNR. In this work, we proposed a novel framework, which integrates the non-local procedure into SAR tomography inversion and combines the robust estimation. A large-scale demonstration has been carried out with five TanDEM-X bistatic data, which covers the entire city of Munich, Germany. Quantitative evaluation of the reconstructed result with the LiDAR reference exhibits the standard deviation of the height difference is within two meters, which implies the proposed framework has great potential for high quality large-scale 3-D urban modeling.
elib-URL des Eintrags: | https://elib.dlr.de/140937/ | ||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||
Titel: | Generation of Large-Scale High Quality 3-D Urban Models | ||||||||||||||||||||
Autoren: |
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Datum: | September 2020 | ||||||||||||||||||||
Erschienen in: | 2020 IEEE Radar Conference, RadarConf 2020 | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||
DOI: | 10.1109/RadarConf2043947.2020.9266314 | ||||||||||||||||||||
Seitenbereich: | Seiten 1-6 | ||||||||||||||||||||
ISSN: | 1097-5659 | ||||||||||||||||||||
ISBN: | 978-172818942-0 | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | 3-D urban models, InSAR, TomoSAR, TanDEM-X, global mapping | ||||||||||||||||||||
Veranstaltungstitel: | 2020 IEEE Radar Conference | ||||||||||||||||||||
Veranstaltungsort: | virtual | ||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
Veranstaltungsbeginn: | 21 September 2020 | ||||||||||||||||||||
Veranstaltungsende: | 25 September 2020 | ||||||||||||||||||||
Veranstalter : | IEEE | ||||||||||||||||||||
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 - Vorhaben hochauflösende Fernerkundungsverfahren (alt), R - SAR-Methoden | ||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > Leitungsbereich MF Institut für Methodik der Fernerkundung > EO Data Science | ||||||||||||||||||||
Hinterlegt von: | Bierkamp-Michalak, Bettina | ||||||||||||||||||||
Hinterlegt am: | 12 Feb 2021 15:26 | ||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:41 |
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