FDA-3D-SAR imaging based on Bayesian compressed sensing
- Resource Type
- Conference
- Authors
- Zhang, Jing; Liao, Ke Fei; Ren, Wen Xin; Shi, Xing Xiang
- Source
- 2021 CIE International Conference on Radar (Radar) Radar (Radar), 2021 CIE International Conference on. :1968-1971 Dec, 2021
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Computing and Processing
Fields, Waves and Electromagnetics
Geoscience
Robotics and Control Systems
Signal Processing and Analysis
Imaging
Scattering
Radar imaging
Frequency diversity
Bayes methods
Arrays
Image reconstruction
BCS
FDA
3D-SAR
- Language
- ISSN
- 2640-7736
In view of the large amount of data to be processed by the Frequency Diversity Array three-dimensional Synthetic Aperture Radar (FDA-3D-SAR) system and the higher side lobes of traditional imaging algorithms, this paper proposes a FDA-3D-SAR imaging method based on Bayesian compressed sensing (BCS) reconstruction. This method combines the characteristics of the FDA to make three-dimensional sparse observation of the target. In the imaging part, the BCS algorithm is used to reconstruct the scattering coefficient of the space target. The experimental results show that the proposed method effectively suppresses the side lobes of the radar image and improves the imaging quality.