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Modelling Ship Detectability Depending On TerraSAR-X-derived Metocean Parameters

Tings, Björn and Bentes da Silva, Carlos Augusto and Velotto, Domenico and Voinov, Sergey (2019) Modelling Ship Detectability Depending On TerraSAR-X-derived Metocean Parameters. CEAS Space Journal, 11 (1), pp. 81-94. Springer. DOI: 10.1007/s12567-018-0222-8 ISBN (Online ISSN 1868-2510) ISSN 1868-2502

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Official URL: https://doi.org/10.1007/s12567-018-0222-8

Abstract

Different metocean conditions have an impact on the detectability of ship signatures on Synthetic Aperture Radar (SAR) images. During the EMSec Project algorithms for retrieval of wind and sea state fields from TerraSAR-X data have been developed in conjunction with a near real-time-capable constant false alarm rate ship detection processor. This paper presents a new model connecting these three information extraction systems into a ship detectability model by setting the probability of detection in dependency to the four parameters: Wind speed, significant wave height, incidence angle and ship length. The model is based on a binary L2-regularized logistic regression classifier trained on a large dataset of X-band SAR ship samples, which are identified using Automatic Identification System messages co-located automatically in space and time and further checked manually to avoid possible mismatches. Results are compared to the state-of-the-art simulation-based ship detectability model available in literature. For the first time it has been possible to evaluate not only qualitatively but also quantitatively the effects of acquisition geometry and metocean conditions for the different image resolution classes obtainable with the high-flexible SAR sensor on-board the TerraSAR-X satellite.

Item URL in elib:https://elib.dlr.de/111712/
Document Type:Article
Additional Information:Open Access Cite this article as: Tings, B., Bentes, C., Velotto, D. et al. CEAS Space J (2019) 11: 81. https://doi.org/10.1007/s12567-018-0222-8 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Title:Modelling Ship Detectability Depending On TerraSAR-X-derived Metocean Parameters
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Tings, BjörnBjoern.Tings (at) dlr.dehttps://orcid.org/0000-0002-1945-6433
Bentes da Silva, Carlos AugustoTechnische Universität München, Arcisstraße 21, 80333 Münchenhttps://orcid.org/0000-0002-5941-334X
Velotto, DomenicoDomenico.Velotto (at) dlr.dehttps://orcid.org/0000-0002-8592-0652
Voinov, SergeySergey.Voinov (at) dlr.dehttps://orcid.org/0000-0003-1511-9728
Date:2019
Journal or Publication Title:CEAS Space Journal
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:11
DOI :10.1007/s12567-018-0222-8
Page Range:pp. 81-94
Publisher:Springer
Series Name:Special Issue on EMSec – Real Time Services for Maritime Safety and Security
ISSN:1868-2502
ISBN:(Online ISSN 1868-2510)
Status:Published
Keywords:ship detection, probability of detection, machine learning, Synthetic Aperture Radar
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - SAR-Methodology
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 2018 10:06
Last Modified:14 Dec 2019 04:28

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