Characterizing the Statistical Properties of SAR Clutter by Using an Empirical Distribution
The performances on the applications of synthetic aperture radar (SAR) data strongly depend on the statistical characteristics of the pixel amplitudes or intensities. In this paper, a new empirical model, called simply ℋ𝒢o, has been proposed to characterize the statistical properties of SAR clutter...
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Format: | Article |
Language: | English |
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Wiley
2013-01-01
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Series: | International Journal of Antennas and Propagation |
Online Access: | http://dx.doi.org/10.1155/2013/109145 |
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author | Gui Gao Gongtao Shi Huanxin Zou Shilin Zhou |
author_facet | Gui Gao Gongtao Shi Huanxin Zou Shilin Zhou |
author_sort | Gui Gao |
collection | DOAJ |
description | The performances on the applications of synthetic aperture radar (SAR) data strongly depend on the statistical characteristics of the pixel amplitudes or intensities. In this paper, a new empirical model, called simply ℋ𝒢o, has been proposed to characterize the statistical properties of SAR clutter data over the wide range of homogeneous, heterogeneous, and extremely heterogeneous returns of terrain classes. A particular case of the ℋ𝒢odistribution is the well-known 𝒢o distributions. We also derived analytically the estimators of the presented ℋ𝒢o model by applying the “method of log cumulants” (MoLCs). The performance of the proposed model is verified by using some measured SAR images. |
format | Article |
id | doaj-art-7fb65e54e3f6421b9b480e101e2c053c |
institution | Kabale University |
issn | 1687-5869 1687-5877 |
language | English |
publishDate | 2013-01-01 |
publisher | Wiley |
record_format | Article |
series | International Journal of Antennas and Propagation |
spelling | doaj-art-7fb65e54e3f6421b9b480e101e2c053c2025-02-03T05:45:05ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772013-01-01201310.1155/2013/109145109145Characterizing the Statistical Properties of SAR Clutter by Using an Empirical DistributionGui Gao0Gongtao Shi1Huanxin Zou2Shilin Zhou3School of Electronics Science and Engineering, National University of Defense Technology, Changsha, Hunan 410073, ChinaSchool of Electronics Science and Engineering, National University of Defense Technology, Changsha, Hunan 410073, ChinaSchool of Electronics Science and Engineering, National University of Defense Technology, Changsha, Hunan 410073, ChinaSchool of Electronics Science and Engineering, National University of Defense Technology, Changsha, Hunan 410073, ChinaThe performances on the applications of synthetic aperture radar (SAR) data strongly depend on the statistical characteristics of the pixel amplitudes or intensities. In this paper, a new empirical model, called simply ℋ𝒢o, has been proposed to characterize the statistical properties of SAR clutter data over the wide range of homogeneous, heterogeneous, and extremely heterogeneous returns of terrain classes. A particular case of the ℋ𝒢odistribution is the well-known 𝒢o distributions. We also derived analytically the estimators of the presented ℋ𝒢o model by applying the “method of log cumulants” (MoLCs). The performance of the proposed model is verified by using some measured SAR images.http://dx.doi.org/10.1155/2013/109145 |
spellingShingle | Gui Gao Gongtao Shi Huanxin Zou Shilin Zhou Characterizing the Statistical Properties of SAR Clutter by Using an Empirical Distribution International Journal of Antennas and Propagation |
title | Characterizing the Statistical Properties of SAR Clutter by Using an Empirical Distribution |
title_full | Characterizing the Statistical Properties of SAR Clutter by Using an Empirical Distribution |
title_fullStr | Characterizing the Statistical Properties of SAR Clutter by Using an Empirical Distribution |
title_full_unstemmed | Characterizing the Statistical Properties of SAR Clutter by Using an Empirical Distribution |
title_short | Characterizing the Statistical Properties of SAR Clutter by Using an Empirical Distribution |
title_sort | characterizing the statistical properties of sar clutter by using an empirical distribution |
url | http://dx.doi.org/10.1155/2013/109145 |
work_keys_str_mv | AT guigao characterizingthestatisticalpropertiesofsarclutterbyusinganempiricaldistribution AT gongtaoshi characterizingthestatisticalpropertiesofsarclutterbyusinganempiricaldistribution AT huanxinzou characterizingthestatisticalpropertiesofsarclutterbyusinganempiricaldistribution AT shilinzhou characterizingthestatisticalpropertiesofsarclutterbyusinganempiricaldistribution |