Omega-KA-Net: A SAR Ground Moving Target Imaging Network Based on Trainable Omega-K Algorithm and Sparse Optimization
The ground moving target (GMT) is defocused due to unknown motion parameters in synthetic aperture radar (SAR) imaging. Although the conventional Omega-K algorithm (Omega-KA) has been proven to be applicable for GMT imaging, its disadvantages are slow imaging speed, obvious sidelobe interference, an...
Main Authors: | Hongwei Zhang, Jiacheng Ni, Shichao Xiong, Ying Luo, Qun Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-03-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/14/7/1664 |
Similar Items
-
Sparse SAR Imaging Method for Ground Moving Target via GMTSI-Net
by: Luwei Chen, et al.
Published: (2022-09-01) -
Robust Clutter Suppression and Ground Moving Target Imaging Method for a Multichannel SAR with High-Squint Angle Mounted on Hypersonic Vehicle
by: Jiusheng Han, et al.
Published: (2021-05-01) -
Maneuvering target imaging and scaling by using sparse inverse synthetic aperture
by: Xu, Gang, et al.
Published: (2017) -
ISAR Imaging of Non-Stationary Moving Target Based on Parameter Estimation and Sparse Decomposition
by: Can Liu, et al.
Published: (2023-04-01) -
A Novel Modified Omega-K Algorithm for Synthetic Aperture Imaging Lidar through the Atmosphere
by: Jing Dan, et al.
Published: (2008-05-01)