Name
Title | ||
|---|---|---|
Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer |
Abstract | ||
|---|---|---|
Millimeter wave synthetic aperture interferometric radiometers (SAIR) are very powerful instruments, which can effectively realize high-precision imaging detection. However due to the existence of interference factor and complex near-field error, the imaging effect of near-field SAIR is usually not ideal. To achieve better imaging results, a new fully connected imaging network (FCIN) is proposed for near-field SAIR. In FCIN, the fully connected network is first used to reconstruct the image domain directly from the visibility function, and then the residual dense network is used for image denoising and enhancement. The simulation results show that the proposed FCIN method has high imaging accuracy and shorten imaging time. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1587/transinf.2021EDL8105 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | DocType | Volume |
fully connected, near field, synthetic aperture radiometer, imaging algorithm, sparse reconstruction | Journal | E105D |
Issue | ISSN | Citations |
5 | 1745-1361 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhimin Guo | 1 | 0 | 0.34 |
| Jianfei Chen | 2 | 0 | 0.34 |
| Sheng Zhang | 3 | 0 | 0.34 |