Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR
This article presents a novel method using a closed-form solution derived from the first, second and third moments to estimate the parameters of K-distribution probability density function (PDF) and its applications to ship detection using dual-polarization synthetic aperture radar (SAR) data. Two k...
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ftdoajarticles:oai:doaj.org/article:ac91ada38ec7442e9b61f72c0478397e 2023-11-12T04:26:04+01:00 Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR Chen Liu 2018-07-01T00:00:00Z https://doi.org/10.1080/07038992.2018.1491789 https://doaj.org/article/ac91ada38ec7442e9b61f72c0478397e EN FR eng fre Taylor & Francis Group http://dx.doi.org/10.1080/07038992.2018.1491789 https://doaj.org/toc/1712-7971 1712-7971 doi:10.1080/07038992.2018.1491789 https://doaj.org/article/ac91ada38ec7442e9b61f72c0478397e Canadian Journal of Remote Sensing, Vol 44, Iss 4, Pp 299-310 (2018) Environmental sciences GE1-350 Technology T article 2018 ftdoajarticles https://doi.org/10.1080/07038992.2018.1491789 2023-10-15T00:36:32Z This article presents a novel method using a closed-form solution derived from the first, second and third moments to estimate the parameters of K-distribution probability density function (PDF) and its applications to ship detection using dual-polarization synthetic aperture radar (SAR) data. Two key parameters which define a K-distribution PDF, equivalent number of independent looks (ENIL, L) and order parameter (ν), can be simultaneously estimated. The derivation has been provided and the applications to ship detection have been described with emphasis on K-distribution function to model ocean samples from a combined dual-polarization system for ship detection. This method along with its applications to ship detection has been thoroughly evaluated with RADARSAT-2 data. This article also presents the knowledge-based target discrimination methods to reduce false alarms when detection is applied to the ocean environment in the presence of sea ice. The detection results were evaluated using the Automatic Identification System (AIS) data. RÉSUMÉ Le présent document porte sur une nouvelle méthode reposant sur l’utilisation d’une solution analytique issue des 1er, 2e et 3e moments pour estimer les paramètres d’une fonction de densité de probabilité (FDP) à distribution k, ainsi que ses applications en matière de détection de navire, au moyen de données de radar à synthèse d’ouverture/à polarisation double. On peut estimer simultanément deux paramètres clés selon lesquels la FDP à distribution k est définie, soit un nombre équivalent de points de vue indépendants (ENIL, L) et un paramètre d’ordre (ν). La fonction dérivée est présentée et les applications en matière de détection de navire, décrites en mettant l’accent sur l’utilisation d’une fonction à distribution k pour modéliser des échantillons océaniques avec un systéme à polarisation double de détection de navire. La méthode décrite et ses applications sur le plan de la détection de navire ont été évaluées de manière approfondie à l’aide de données de ... Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Canadian Journal of Remote Sensing 44 4 299 310 |
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Environmental sciences GE1-350 Technology T |
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Environmental sciences GE1-350 Technology T Chen Liu Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR |
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Environmental sciences GE1-350 Technology T |
description |
This article presents a novel method using a closed-form solution derived from the first, second and third moments to estimate the parameters of K-distribution probability density function (PDF) and its applications to ship detection using dual-polarization synthetic aperture radar (SAR) data. Two key parameters which define a K-distribution PDF, equivalent number of independent looks (ENIL, L) and order parameter (ν), can be simultaneously estimated. The derivation has been provided and the applications to ship detection have been described with emphasis on K-distribution function to model ocean samples from a combined dual-polarization system for ship detection. This method along with its applications to ship detection has been thoroughly evaluated with RADARSAT-2 data. This article also presents the knowledge-based target discrimination methods to reduce false alarms when detection is applied to the ocean environment in the presence of sea ice. The detection results were evaluated using the Automatic Identification System (AIS) data. RÉSUMÉ Le présent document porte sur une nouvelle méthode reposant sur l’utilisation d’une solution analytique issue des 1er, 2e et 3e moments pour estimer les paramètres d’une fonction de densité de probabilité (FDP) à distribution k, ainsi que ses applications en matière de détection de navire, au moyen de données de radar à synthèse d’ouverture/à polarisation double. On peut estimer simultanément deux paramètres clés selon lesquels la FDP à distribution k est définie, soit un nombre équivalent de points de vue indépendants (ENIL, L) et un paramètre d’ordre (ν). La fonction dérivée est présentée et les applications en matière de détection de navire, décrites en mettant l’accent sur l’utilisation d’une fonction à distribution k pour modéliser des échantillons océaniques avec un systéme à polarisation double de détection de navire. La méthode décrite et ses applications sur le plan de la détection de navire ont été évaluées de manière approfondie à l’aide de données de ... |
format |
Article in Journal/Newspaper |
author |
Chen Liu |
author_facet |
Chen Liu |
author_sort |
Chen Liu |
title |
Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR |
title_short |
Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR |
title_full |
Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR |
title_fullStr |
Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR |
title_full_unstemmed |
Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR |
title_sort |
method for fitting k-distributed probability density function to ocean pixels in dual-polarization sar |
publisher |
Taylor & Francis Group |
publishDate |
2018 |
url |
https://doi.org/10.1080/07038992.2018.1491789 https://doaj.org/article/ac91ada38ec7442e9b61f72c0478397e |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Canadian Journal of Remote Sensing, Vol 44, Iss 4, Pp 299-310 (2018) |
op_relation |
http://dx.doi.org/10.1080/07038992.2018.1491789 https://doaj.org/toc/1712-7971 1712-7971 doi:10.1080/07038992.2018.1491789 https://doaj.org/article/ac91ada38ec7442e9b61f72c0478397e |
op_doi |
https://doi.org/10.1080/07038992.2018.1491789 |
container_title |
Canadian Journal of Remote Sensing |
container_volume |
44 |
container_issue |
4 |
container_start_page |
299 |
op_container_end_page |
310 |
_version_ |
1782340202358898688 |