Characterization and Removal of RFI Artifacts in Radar Data via Model-Constrained Deep Learning Approach
Microwave remote sensing instruments such as synthetic aperture radar (SAR) play an important role in scientific research applications, while they suffer great measurement distortion with the presence of radio frequency interference (RFI). Existing methods either adopt model−based optimization or fo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-03-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/7/1578 |