Iterative Regularization Using an Acceleration Technique for Synthetic Aperture Interferometric Radiometer
The inverse problem of synthetic aperture interferometric radiometers (SAIRs) aims at retrieving the brightness temperature map from the visibility function samples. To efficiently obtain an accurate solution, an accelerated iterative regularization technique is proposed to reconstruct the SAIR brig...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10124977/ |
| Summary: | The inverse problem of synthetic aperture interferometric radiometers (SAIRs) aims at retrieving the brightness temperature map from the visibility function samples. To efficiently obtain an accurate solution, an accelerated iterative regularization technique is proposed to reconstruct the SAIR brightness temperature map. The acceleration technique modifies the conventional least square function using a negative penalty term to speed up the initial iterations. A series of decreasing coefficients must be tuned to prevent noise amplification in subsequent iterations. Several numerical experiments were performed on one-dimensional (1-D) and (2-D) SAIR systems. The experiment results indicate that the accelerated Landweber method reduces the number of iteration steps by more than 50% and effectively improves the computational speed without reducing the reconstruction accuracy compared to the conventional Landweber method. |
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| ISSN: | 2151-1535 |