Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/225490
Title: AET-IAA: A Novel Approach to Enhance Azimuth Resolution for ScanSAR Interferometry
Authors: Jiaqi Ning;Robert Wang;Yunkai Deng;Ning Li;Huina Song;Wenbo Fei
Year: 2017
Publisher: IEEE
Abstract: Scanning synthetic aperture radar (ScanSAR) obtains wide swath images at the expense of azimuth resolution by sweeping the antenna beam periodically. Interferometric applications benefit from the wide swath of ScanSAR data. As a result, ScanSAR interferometry can efficiently acquire large scale geophysical information. However, the low azimuth resolution of ScanSAR images limits some applications of ScanSAR interferometry in urban areas such as topographic mapping. In this manuscript, an improved azimuth processing algorithm is proposed, which combines linear-prediction-model-based aperture extrapolation technique (AET) with iterative adaptive approach (IAA), entitled as AET-IAA. The AET-IAA can not only enhance the azimuth resolution significantly, but also preserve the phase information of the data. Simulation and experimental results demonstrate that the proposed algorithm outperforms conventional algorithms when used in ScanSAR interferometry in urban areas.
URI: http://localhost/handle/Hannan/225490
volume: 10
issue: 12
More Information: 5674,
5685
Appears in Collections:2017

Files in This Item:
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8038005.pdf3.39 MBAdobe PDF
Title: AET-IAA: A Novel Approach to Enhance Azimuth Resolution for ScanSAR Interferometry
Authors: Jiaqi Ning;Robert Wang;Yunkai Deng;Ning Li;Huina Song;Wenbo Fei
Year: 2017
Publisher: IEEE
Abstract: Scanning synthetic aperture radar (ScanSAR) obtains wide swath images at the expense of azimuth resolution by sweeping the antenna beam periodically. Interferometric applications benefit from the wide swath of ScanSAR data. As a result, ScanSAR interferometry can efficiently acquire large scale geophysical information. However, the low azimuth resolution of ScanSAR images limits some applications of ScanSAR interferometry in urban areas such as topographic mapping. In this manuscript, an improved azimuth processing algorithm is proposed, which combines linear-prediction-model-based aperture extrapolation technique (AET) with iterative adaptive approach (IAA), entitled as AET-IAA. The AET-IAA can not only enhance the azimuth resolution significantly, but also preserve the phase information of the data. Simulation and experimental results demonstrate that the proposed algorithm outperforms conventional algorithms when used in ScanSAR interferometry in urban areas.
URI: http://localhost/handle/Hannan/225490
volume: 10
issue: 12
More Information: 5674,
5685
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8038005.pdf3.39 MBAdobe PDF
Title: AET-IAA: A Novel Approach to Enhance Azimuth Resolution for ScanSAR Interferometry
Authors: Jiaqi Ning;Robert Wang;Yunkai Deng;Ning Li;Huina Song;Wenbo Fei
Year: 2017
Publisher: IEEE
Abstract: Scanning synthetic aperture radar (ScanSAR) obtains wide swath images at the expense of azimuth resolution by sweeping the antenna beam periodically. Interferometric applications benefit from the wide swath of ScanSAR data. As a result, ScanSAR interferometry can efficiently acquire large scale geophysical information. However, the low azimuth resolution of ScanSAR images limits some applications of ScanSAR interferometry in urban areas such as topographic mapping. In this manuscript, an improved azimuth processing algorithm is proposed, which combines linear-prediction-model-based aperture extrapolation technique (AET) with iterative adaptive approach (IAA), entitled as AET-IAA. The AET-IAA can not only enhance the azimuth resolution significantly, but also preserve the phase information of the data. Simulation and experimental results demonstrate that the proposed algorithm outperforms conventional algorithms when used in ScanSAR interferometry in urban areas.
URI: http://localhost/handle/Hannan/225490
volume: 10
issue: 12
More Information: 5674,
5685
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8038005.pdf3.39 MBAdobe PDF