A Deep Learning Method for SAR Imaging in Sparse Field
2021
Motivated by the successes of data driven approaches in various fields, a great number of deep learning methods have been applied to SAR images. In this work, we propose a deep neural network named RG-Net, which can generate SAR images from raw echo data in the sparse target domain. Experiments are carried out on a simulation dataset, and the results show the superiority of the proposed method on imaging quality and computational efficiency. The source code is at https://github.com/zhangyingerjelly/RG-Net
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
3
References
0
Citations
NaN
KQI