DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Comparison of ship detectability between TerraSAR-X and Sentinel-1

Velotto, Domenico and Tings, Björn and Bentes da Silva, Carlos Augusto (2017) Comparison of ship detectability between TerraSAR-X and Sentinel-1. In: Proceedings of the 3rd International Forum on Research and Technologies for Society and Industry (RTSI), pp. 1-5. IEEE. 3rd International Forum on Research and Technologies for Society and Industry (RTSI), 11-13 Sept. 2017, Modena, Italy. doi: 10.1109/RTSI.2017.8065913.

[img] PDF

Official URL: https://doi.org/10.1109/RTSI.2017.8065913


In this paper, the detectability of ship signatures in Synthetic Aperture Radar (SAR) imagery acquired by the TerraSAR X/TanDEM-X and Sentinel 1 is compared. The comparison takes into account different sensors acquisition parameters and environmental conditions on a large variety of ship size and types. In the first step, ocean targets are detected using the Near Real Time (NRT)-optimized Constant-False-Alarm-Rate (CFAR) algorithm. The optimizations include the ocean/land and false targets discrimination. In the second step, all detected targets are automatically matched in space and time with the recorded Automatic Identification System (AIS) messages. A manual cross-check is performed at the end of the assignments to have a clean SAR ship signature database. Additionally, the local wind field is retrieved from the SAR backscatter of the ocean surface surrounding the detected ships, by applying the Geophysical Model Functions (GMF) inversion XMOD2 for X-band data and CMOD5 for C-band data. Similarly, the local sea state conditions are calculated by the XWAVE and CWAVE empirical model functions. The final detectability model takes into account all SAR-based information, i.e. wind speed and sea state, as well as relevant SAR parameters, e.g. incidence angle. The overall probability of detection are derived for three ship size categories, i.e. small, medium and large, adopting an L2-regularized Logistic Regression classifier trained on detected and nondetected ship samples.

Item URL in elib:https://elib.dlr.de/112265/
Document Type:Conference or Workshop Item (Speech)
Additional Information:Conference: http://rtsi2017.ieeesezioneitalia.it/tech_sess.html
Title:Comparison of ship detectability between TerraSAR-X and Sentinel-1
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Velotto, DomenicoDomenico.Velotto (at) dlr.dehttps://orcid.org/0000-0002-8592-0652
Tings, BjörnBjoern.Tings (at) dlr.dehttps://orcid.org/0000-0002-1945-6433
Bentes da Silva, Carlos Augustocarlos.bentes (at) tum.dehttps://orcid.org/0000-0002-5941-334X
Date:12 October 2017
Journal or Publication Title:Proceedings of the 3rd International Forum on Research and Technologies for Society and Industry (RTSI)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
DOI :10.1109/RTSI.2017.8065913
Page Range:pp. 1-5
Series Name:IEEE Xplore
Keywords:TerraSAR-X, Sentinel-1, SAR, ship detectability
Event Title:3rd International Forum on Research and Technologies for Society and Industry (RTSI)
Event Location:Modena, Italy
Event Type:international Conference
Event Dates:11-13 Sept. 2017
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 , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Kaps, Ruth
Deposited On:08 Dec 2017 11:30
Last Modified:31 Jul 2019 20:09

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.