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Reduction of the Reconstruction Error With Lower and Upper Bounds in Synthetic Aperture Imaging Radiometers
- Source :
- IEEE Access, Vol 8, Pp 156964-156971 (2020)
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- Synthetic aperture imaging radiometers (SAIRs) are powerful instruments for high-resolution Earth observation by use of small-aperture antennas sparsely arranged to achieve a large-aperture antenna. High-precision reconstruction algorithm is one of the key contents of SAIRs. Owing to the ill-posed problem and band-limited physical characteristic, there is a still large residual error for traditional regularization methods. It should be noted that the prior information like the lower and upper bounds of the brightness temperature distributions has not been utilized in the reconstruction procedure, especially for the open ocean with relatively small brightness temperature difference. In order to reduce the reconstruction error in SAIRs, a reconstruction method based on active set algorithm is presented by solving the least squares problems with lower and upper bounds. The simulation experiment results show that the proposed method can more effectively reduce the reconstruction error and better improve the accuracy of retrieved brightness temperature distributions in SAIRs than the band-limited regularization method, demonstrating the effectiveness of the proposed method.
- Subjects :
- synthetic aperture
Radiometer
010504 meteorology & atmospheric sciences
General Computer Science
Computer science
0211 other engineering and technologies
General Engineering
Reconstruction algorithm
02 engineering and technology
Residual
reconstruction error
01 natural sciences
Least squares
Regularization (mathematics)
Reduction (complexity)
Imaging radiometry
Brightness temperature
inverse problem
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
lcsh:TK1-9971
Reconstruction procedure
Algorithm
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....0f4574753468cf20eaa48beb4a113a94