Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation

Parabolic-reflector antennas (PRAs), usually possessing rotation, are a particular type of targets of potential interest to the synthetic aperture radar (SAR) community. This paper is aimed to investigate PRA’s scattering characteristics and then to extract PRA’s parameters from SAR returns, for sup...

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Main Authors: Bin Deng, Hong-Qiang Wang, Yu-Liang Qin, Sha Zhu, Xiang Li
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:International Journal of Antennas and Propagation
Online Access:http://dx.doi.org/10.1155/2013/583865
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author Bin Deng
Hong-Qiang Wang
Yu-Liang Qin
Sha Zhu
Xiang Li
author_facet Bin Deng
Hong-Qiang Wang
Yu-Liang Qin
Sha Zhu
Xiang Li
author_sort Bin Deng
collection DOAJ
description Parabolic-reflector antennas (PRAs), usually possessing rotation, are a particular type of targets of potential interest to the synthetic aperture radar (SAR) community. This paper is aimed to investigate PRA’s scattering characteristics and then to extract PRA’s parameters from SAR returns, for supporting image interpretation and target recognition. We at first obtain both closed-form and numeric solutions to PRA’s backscattering by geometrical optics (GO), physical optics, and graphical electromagnetic computation, respectively. Based on the GO solution, a migratory scattering center model is at first presented for representing the movement of the specular point with aspect angle, and then a hybrid model, named the migratory/micromotion scattering center (MMSC) model, is proposed for characterizing a rotating PRA in the SAR geometry, which incorporates PRA’s rotation into its migratory scattering center model. Additionally, we in detail analyze PRA’s radar characteristics on radar cross-section, high-resolution range profiles, time-frequency distribution, and 2D images, which also confirm the models proposed. A maximal likelihood estimator is developed for jointly solving the MMSC model for PRA’s multiple parameters by optimization. By exploiting the aforementioned characteristics, the coarse parameter estimation guarantees convergency upon global minima. The signatures recovered can be favorably utilized for SAR image interpretation and target recognition.
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issn 1687-5869
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language English
publishDate 2013-01-01
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series International Journal of Antennas and Propagation
spelling doaj-art-fd3143499e0e4dc88a76824fdfd7588b2025-08-20T02:22:40ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772013-01-01201310.1155/2013/583865583865Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter EstimationBin Deng0Hong-Qiang Wang1Yu-Liang Qin2Sha Zhu3Xiang Li4College of Electronic Science and Engineering, National University of Defense Technology, ChinaCollege of Electronic Science and Engineering, National University of Defense Technology, ChinaCollege of Electronic Science and Engineering, National University of Defense Technology, ChinaCollege of Electronic Science and Engineering, National University of Defense Technology, ChinaCollege of Electronic Science and Engineering, National University of Defense Technology, ChinaParabolic-reflector antennas (PRAs), usually possessing rotation, are a particular type of targets of potential interest to the synthetic aperture radar (SAR) community. This paper is aimed to investigate PRA’s scattering characteristics and then to extract PRA’s parameters from SAR returns, for supporting image interpretation and target recognition. We at first obtain both closed-form and numeric solutions to PRA’s backscattering by geometrical optics (GO), physical optics, and graphical electromagnetic computation, respectively. Based on the GO solution, a migratory scattering center model is at first presented for representing the movement of the specular point with aspect angle, and then a hybrid model, named the migratory/micromotion scattering center (MMSC) model, is proposed for characterizing a rotating PRA in the SAR geometry, which incorporates PRA’s rotation into its migratory scattering center model. Additionally, we in detail analyze PRA’s radar characteristics on radar cross-section, high-resolution range profiles, time-frequency distribution, and 2D images, which also confirm the models proposed. A maximal likelihood estimator is developed for jointly solving the MMSC model for PRA’s multiple parameters by optimization. By exploiting the aforementioned characteristics, the coarse parameter estimation guarantees convergency upon global minima. The signatures recovered can be favorably utilized for SAR image interpretation and target recognition.http://dx.doi.org/10.1155/2013/583865
spellingShingle Bin Deng
Hong-Qiang Wang
Yu-Liang Qin
Sha Zhu
Xiang Li
Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation
International Journal of Antennas and Propagation
title Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation
title_full Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation
title_fullStr Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation
title_full_unstemmed Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation
title_short Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation
title_sort rotating parabolic reflector antenna target in sar data model characteristics and parameter estimation
url http://dx.doi.org/10.1155/2013/583865
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AT hongqiangwang rotatingparabolicreflectorantennatargetinsardatamodelcharacteristicsandparameterestimation
AT yuliangqin rotatingparabolicreflectorantennatargetinsardatamodelcharacteristicsandparameterestimation
AT shazhu rotatingparabolicreflectorantennatargetinsardatamodelcharacteristicsandparameterestimation
AT xiangli rotatingparabolicreflectorantennatargetinsardatamodelcharacteristicsandparameterestimation