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Dynamically adapted ship parameter estimation on TerraSAR-X images

Tings, Björn and Bentes da Silva, Carlos Augusto and Lehner, Susanne (2015) Dynamically adapted ship parameter estimation on TerraSAR-X images. International Journal of Remote Sensing, 37 (9), pp. 1990-2015. Taylor & Francis. doi: 10.1080/01431161.2015.1071898. ISSN 0143-1161.

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Official URL: http://dx.doi.org/10.1080/01431161.2015.1071898


This article describes how the estimation of ship parameters from ship signatures on TerraSAR-X images can be improved dynamically using combinatorial optimization and regression analysis. Research in the field of ship detection commonly addresses the improvement of processors with regard to accuracy performance of detection and of parameter estimation. While most research implies beneficial improvements to the processors, the different techniques are rarely compared or combined. In this article Monte-Carlo combinatorial optimization (cross-entropy method) is used to evaluate the performance of improvements to parameter estimation and the performance of combinations of these improvements. Then multiple linear regression analysis is applied to increase the accuracy of parameter estimation further. The underlying data set consists of TerraSAR X Stripmap, ScanSAR and ScanSAR Wide multi-look ground-range detected (MGD) images acquired over North Sea and Baltic Sea with HH or VV polarization. Validation data is provided by the Automatic Identification System (AIS). The optimization algorithm assesses optimal parameter settings and appropriate combinations of techniques dedicated to this dataset. The resulting processor provides a significantly higher accuracy of ship parameter estimation.

Item URL in elib:https://elib.dlr.de/95922/
Document Type:Article
Additional Information:12th Biennial Conference of Pan Ocean Remote Sensing Conference (PORSEC 2014)//04 – 07 November 2014, Bali-Indonesia//published online 25 Aug 2015// *Corresponding author. Email: bjoern.tings@dlr.de
Title:Dynamically adapted ship parameter estimation on TerraSAR-X images
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Tings, BjörnBjoern.Tings (at) dlr.dehttps://orcid.org/0000-0002-1945-6433
Bentes da Silva, Carlos AugustoCarlos.Bentes (at) dlr.dehttps://orcid.org/0000-0002-5941-334X
Lehner, SusanneSusanne.Lehner (at) dlr.deUNSPECIFIED
Journal or Publication Title:International Journal of Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1080/01431161.2015.1071898
Page Range:pp. 1990-2015
Publisher:Taylor & Francis
Series Name:Special Issue: Ocean remote sensing for sustainable resources
Keywords:ship detection; ship parameter estimation; machine learning; image processing, 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 - Earth Observation
DLR - Research theme (Project):R - Vorhaben Entwicklung und Erprobung von Verfahren zur Gewässerfernerkundung (old)
Location: Bremen , Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Remote Sensing Technology Institute
Deposited By: Kaps, Ruth
Deposited On:15 Apr 2015 13:52
Last Modified:20 Jul 2016 11:04

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