Incidence angle normalization of Wide Swath SAR data for oceanographic applications
A backscattering trend in the range direction of the signal received by Synthetic Aperture Radar (SAR) in Wide Swath (WS) mode results in a progressive reduction of brightness over images from near to far range, which affects the detection and classification of sea surface features on wide swath SAR...
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doaj-ac05dc9a8e154349a3ed8a3d45a5aa0f2021-09-05T20:50:47ZengDe GruyterOpen Geosciences2391-54472016-08-018145046410.1515/geo-2016-0029geo-2016-0029Incidence angle normalization of Wide Swath SAR data for oceanographic applicationsTopouzelis Konstantinos0Singha Suman1Kitsiou Dimitra2Remote Sensing Technology Institute, German Aerospace Center (DLR), Heinrich Focke Str. 4, 28199 Bremen, GermanyRemote Sensing Technology Institute, German Aerospace Center (DLR), Heinrich Focke Str. 4, 28199 Bremen, GermanyDepartment of Marine Sciences, School of the Environment, University of the Aegean, University Hill, 81100, Mytilini, Lesvos Island, GreeceA backscattering trend in the range direction of the signal received by Synthetic Aperture Radar (SAR) in Wide Swath (WS) mode results in a progressive reduction of brightness over images from near to far range, which affects the detection and classification of sea surface features on wide swath SAR images. The aim of the present paper is to investigate methods for limiting the issue of Normalized Radar Cross-Section (NRCS or σ°) variation due to the incidence angle. Two sensor independent functions are investigated: a theoretical backscattering shape function derived from a minimum wind speed and an empirical range fit of NRCS against incidence angle θ. The former method exploits only the modeled NRCS values while the latter only the image content. The results were compared with the squared cosine correction, the most widely applied method for normalization, using six newly developed comparison factors. The results showed that the cosine squared normalization has the lowest efficiency while the proposed methods have similar behaviors and comparable results. Nevertheless, after the log-transformation and summation of the comparison factors, it was clearly shown that theoretical normalization performance is superior to the empirical one since it has the highest accuracy and requires less computational time.https://doi.org/10.1515/geo-2016-0029oceanoceanic phenomena recognitionasarnormalized radar cross section |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Topouzelis Konstantinos Singha Suman Kitsiou Dimitra |
spellingShingle |
Topouzelis Konstantinos Singha Suman Kitsiou Dimitra Incidence angle normalization of Wide Swath SAR data for oceanographic applications Open Geosciences ocean oceanic phenomena recognition asar normalized radar cross section |
author_facet |
Topouzelis Konstantinos Singha Suman Kitsiou Dimitra |
author_sort |
Topouzelis Konstantinos |
title |
Incidence angle normalization of Wide Swath SAR data for oceanographic applications |
title_short |
Incidence angle normalization of Wide Swath SAR data for oceanographic applications |
title_full |
Incidence angle normalization of Wide Swath SAR data for oceanographic applications |
title_fullStr |
Incidence angle normalization of Wide Swath SAR data for oceanographic applications |
title_full_unstemmed |
Incidence angle normalization of Wide Swath SAR data for oceanographic applications |
title_sort |
incidence angle normalization of wide swath sar data for oceanographic applications |
publisher |
De Gruyter |
series |
Open Geosciences |
issn |
2391-5447 |
publishDate |
2016-08-01 |
description |
A backscattering trend in the range direction of the signal received by Synthetic Aperture Radar (SAR) in Wide Swath (WS) mode results in a progressive reduction of brightness over images from near to far range, which affects the detection and classification of sea surface features on wide swath SAR images. The aim of the present paper is to investigate methods for limiting the issue of Normalized Radar Cross-Section (NRCS or σ°) variation due to the incidence angle. Two sensor independent functions are investigated: a theoretical backscattering shape function derived from a minimum wind speed and an empirical range fit of NRCS against incidence angle θ. The former method exploits only the modeled NRCS values while the latter only the image content. The results were compared with the squared cosine correction, the most widely applied method for normalization, using six newly developed comparison factors. The results showed that the cosine squared normalization has the lowest efficiency while the proposed methods have similar behaviors and comparable results. Nevertheless, after the log-transformation and summation of the comparison factors, it was clearly shown that theoretical normalization performance is superior to the empirical one since it has the highest accuracy and requires less computational time. |
topic |
ocean oceanic phenomena recognition asar normalized radar cross section |
url |
https://doi.org/10.1515/geo-2016-0029 |
work_keys_str_mv |
AT topouzeliskonstantinos incidenceanglenormalizationofwideswathsardataforoceanographicapplications AT singhasuman incidenceanglenormalizationofwideswathsardataforoceanographicapplications AT kitsioudimitra incidenceanglenormalizationofwideswathsardataforoceanographicapplications |
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1717784449338310656 |