Large-Scale Inverse Modeling of Microwave Backscatter from Sea
remundq @ ee.by u.edu, long @ ee.by u.edu Abstruct- Many forward electromagnetic scattering models have been proposed to predict the normalized radar cross section, &', from sea ice characteristics. In this paper, we apply scatterometer data to large scale inverse modeling. Given the limite...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.391.8767 2023-05-15T15:01:12+02:00 Large-Scale Inverse Modeling of Microwave Backscatter from Sea Quinn P. Remund David G. Long The Pennsylvania State University CiteSeerX Archives 2000 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.8767 http://www.mers.byu.edu/long/papers/conf/IGARSS2000JulyRemund2.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.8767 http://www.mers.byu.edu/long/papers/conf/IGARSS2000JulyRemund2.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.mers.byu.edu/long/papers/conf/IGARSS2000JulyRemund2.pdf text 2000 ftciteseerx 2016-01-08T02:17:41Z remundq @ ee.by u.edu, long @ ee.by u.edu Abstruct- Many forward electromagnetic scattering models have been proposed to predict the normalized radar cross section, &', from sea ice characteristics. In this paper, we apply scatterometer data to large scale inverse modeling. Given the limited resolution, we adopt a simple geometric optics forward scattering model to analyze surface and volume scattering contributions to observed Ku-band signatures. A model inversion technique based on recursive optimization of an objective function is developed. Simulations demonstrate the performance of the method in the presence of noise. The inverse model is implemented using Ku-band image reconstructed data collected by the NASA scatterometer. The results are used to analyze and interpret 0 ' phenomena occurring in the Arctic. Text Arctic Sea ice Unknown Arctic |
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English |
description |
remundq @ ee.by u.edu, long @ ee.by u.edu Abstruct- Many forward electromagnetic scattering models have been proposed to predict the normalized radar cross section, &', from sea ice characteristics. In this paper, we apply scatterometer data to large scale inverse modeling. Given the limited resolution, we adopt a simple geometric optics forward scattering model to analyze surface and volume scattering contributions to observed Ku-band signatures. A model inversion technique based on recursive optimization of an objective function is developed. Simulations demonstrate the performance of the method in the presence of noise. The inverse model is implemented using Ku-band image reconstructed data collected by the NASA scatterometer. The results are used to analyze and interpret 0 ' phenomena occurring in the Arctic. |
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The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Quinn P. Remund David G. Long |
spellingShingle |
Quinn P. Remund David G. Long Large-Scale Inverse Modeling of Microwave Backscatter from Sea |
author_facet |
Quinn P. Remund David G. Long |
author_sort |
Quinn P. Remund |
title |
Large-Scale Inverse Modeling of Microwave Backscatter from Sea |
title_short |
Large-Scale Inverse Modeling of Microwave Backscatter from Sea |
title_full |
Large-Scale Inverse Modeling of Microwave Backscatter from Sea |
title_fullStr |
Large-Scale Inverse Modeling of Microwave Backscatter from Sea |
title_full_unstemmed |
Large-Scale Inverse Modeling of Microwave Backscatter from Sea |
title_sort |
large-scale inverse modeling of microwave backscatter from sea |
publishDate |
2000 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.8767 http://www.mers.byu.edu/long/papers/conf/IGARSS2000JulyRemund2.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
http://www.mers.byu.edu/long/papers/conf/IGARSS2000JulyRemund2.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.8767 http://www.mers.byu.edu/long/papers/conf/IGARSS2000JulyRemund2.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
_version_ |
1766333231364308992 |