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X-Band/C-Band-Comparison of Ship Wake Detectability

Tings, Björn and Jacobsen, Sven and Wiehle, Stefan and Schwarz, Egbert and Daedelow, Holger (2021) X-Band/C-Band-Comparison of Ship Wake Detectability. In: 13th European Conference on Synthetic Aperture Radar, EUSAR 2021, pp. 700-704. IEEE. EUSAR 2021, 29. Mar - 01. Apr 2021, online. ISBN 978-3-8007-5457-1. ISSN 2197-4403.

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Official URL: https://ieeexplore.ieee.org/document/9472637

Abstract

This study presents an extension to recent ship wake detectability models based on SAR image analysis with machine learning. In contrast to our previous works, we model the detectability of certain wake components individually. The underlying data set is obtained by extracting possible ship wake signatures from SAR imagery by collocation with Automatic Identification System data. The developed detectability models are based on machine learning. They generally confirm previous findings based on simulated SAR data or qualitative image analysis. The results from our previous wake detectability model are compared to initial results from our new wake component detectability model.

Item URL in elib:https://elib.dlr.de/134596/
Document Type:Conference or Workshop Item (Speech)
Title:X-Band/C-Band-Comparison of Ship Wake Detectability
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Tings, BjörnBjoern.Tings (at) dlr.dehttps://orcid.org/0000-0002-1945-6433
Jacobsen, SvenSven.Jacobsen (at) dlr.dehttps://orcid.org/0000-0003-4810-4186
Wiehle, StefanStefan.Wiehle (at) dlr.dehttps://orcid.org/0000-0003-1476-6261
Schwarz, EgbertEgbert.Schwarz (at) dlr.deUNSPECIFIED
Daedelow, HolgerHolger.Daedelow (at) dlr.deUNSPECIFIED
Date:31 March 2021
Journal or Publication Title:13th European Conference on Synthetic Aperture Radar, EUSAR 2021
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Page Range:pp. 700-704
Editors:
EditorsEmailEditor's ORCID iD
UNSPECIFIEDVDEUNSPECIFIED
Publisher:IEEE
ISSN:2197-4403
ISBN:978-3-8007-5457-1
Status:Published
Keywords:Synthetic Aperture Radar; wake detection; detectability model; machine learning; Support Vector Machine; ocean surface imaging
Event Title:EUSAR 2021
Event Location:online
Event Type:international Conference
Event Dates:29. Mar - 01. Apr 2021
Organizer:VDE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - SAR methods
Location: Bremen , Neustrelitz , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
German Remote Sensing Data Center > National Ground Segment
Deposited By: Kaps, Ruth
Deposited On:27 Nov 2020 10:28
Last Modified:13 Jul 2021 13:54

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