Reduction of the Instrument Model Error in Aperture Synthesis Radiometers

Aperture synthesis radiometers measure the visibilities of the scene under observation by an antenna array, and based on these visibility measurements, inverse algorithm is employed to reconstruct the brightness temperature of the observed scene. The instrument model plays a key role in the inverse...

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Main Authors: Xiaohui Peng, Fei Hu, Dong Zhu, Yayun Cheng, Tao Zheng, Hao Hu
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8264707/
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author Xiaohui Peng
Fei Hu
Dong Zhu
Yayun Cheng
Tao Zheng
Hao Hu
author_facet Xiaohui Peng
Fei Hu
Dong Zhu
Yayun Cheng
Tao Zheng
Hao Hu
author_sort Xiaohui Peng
collection DOAJ
description Aperture synthesis radiometers measure the visibilities of the scene under observation by an antenna array, and based on these visibility measurements, inverse algorithm is employed to reconstruct the brightness temperature of the observed scene. The instrument model plays a key role in the inverse problem and its error will degrade the reconstruction accuracy. This work provides an analysis of the impact of the instrument model error on the reconstruction accuracy and a method regarding how to reduce its impact. It will be demonstrated in this work that the point spread functions (PSFs) of the imaging system at different spatial locations are highly correlated with each other, but the PSF errors are not. Benefit from this fact, the PSF can be represented as a sum of basis functions obtained from principal component analysis of PSF. It can be observed that most of the energy of the true PSF is concentrated on the first L principal components, and the last N-L principal components can be neglected due to that they are dominated by the noise. Numerical studies are carried out using the data obtained from the Soil Moisture and Ocean Salinity (SMOS) official website, and the corresponding results validate that the proposed method is effective in reducing the instrument model error.
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spelling doaj.art-d00e34614b524233aad09d2b8e9f2a692022-12-21T23:05:59ZengIEEEIEEE Access2169-35362018-01-0169238924610.1109/ACCESS.2018.27955308264707Reduction of the Instrument Model Error in Aperture Synthesis RadiometersXiaohui Peng0https://orcid.org/0000-0002-7410-8538Fei Hu1Dong Zhu2Yayun Cheng3Tao Zheng4Hao Hu5School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, ChinaAperture synthesis radiometers measure the visibilities of the scene under observation by an antenna array, and based on these visibility measurements, inverse algorithm is employed to reconstruct the brightness temperature of the observed scene. The instrument model plays a key role in the inverse problem and its error will degrade the reconstruction accuracy. This work provides an analysis of the impact of the instrument model error on the reconstruction accuracy and a method regarding how to reduce its impact. It will be demonstrated in this work that the point spread functions (PSFs) of the imaging system at different spatial locations are highly correlated with each other, but the PSF errors are not. Benefit from this fact, the PSF can be represented as a sum of basis functions obtained from principal component analysis of PSF. It can be observed that most of the energy of the true PSF is concentrated on the first L principal components, and the last N-L principal components can be neglected due to that they are dominated by the noise. Numerical studies are carried out using the data obtained from the Soil Moisture and Ocean Salinity (SMOS) official website, and the corresponding results validate that the proposed method is effective in reducing the instrument model error.https://ieeexplore.ieee.org/document/8264707/Aperture synthesis radiometers (ASR)instrument model errorprincipal component analysis (PCA)point spread function
spellingShingle Xiaohui Peng
Fei Hu
Dong Zhu
Yayun Cheng
Tao Zheng
Hao Hu
Reduction of the Instrument Model Error in Aperture Synthesis Radiometers
IEEE Access
Aperture synthesis radiometers (ASR)
instrument model error
principal component analysis (PCA)
point spread function
title Reduction of the Instrument Model Error in Aperture Synthesis Radiometers
title_full Reduction of the Instrument Model Error in Aperture Synthesis Radiometers
title_fullStr Reduction of the Instrument Model Error in Aperture Synthesis Radiometers
title_full_unstemmed Reduction of the Instrument Model Error in Aperture Synthesis Radiometers
title_short Reduction of the Instrument Model Error in Aperture Synthesis Radiometers
title_sort reduction of the instrument model error in aperture synthesis radiometers
topic Aperture synthesis radiometers (ASR)
instrument model error
principal component analysis (PCA)
point spread function
url https://ieeexplore.ieee.org/document/8264707/
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AT feihu reductionoftheinstrumentmodelerrorinaperturesynthesisradiometers
AT dongzhu reductionoftheinstrumentmodelerrorinaperturesynthesisradiometers
AT yayuncheng reductionoftheinstrumentmodelerrorinaperturesynthesisradiometers
AT taozheng reductionoftheinstrumentmodelerrorinaperturesynthesisradiometers
AT haohu reductionoftheinstrumentmodelerrorinaperturesynthesisradiometers