Ship Target SAR Dataset Generation Based on Ray Tracing Including Multiple Scattering
In order to improve the fidelity of SAR image simulation for ship target, we propose a novel ship target SAR dataset generation method based on ray tracing including multiple scattering. The method integrates the SAR spatial traversal mode and ray casting theory for discriminating the radar beam radiation areas of ship target and modeling electromagnetic (EM) wave transmissions under the geometric constraints of Range Doppler (RD) imaging geometry. Based on the simulation of EM waves transmission, the ray tracing algorithm and the physical illumination model are combined to simulate the multiple backscattering of EM waves, and the multiple backscattering amplitude and phase are recorded in real time. Then, the total backscattering field of the distributed ship target can be generated by the vector superposition of the multiple backscattering subfields of the EM waves transmitted towards the beam radiation area. Finally, the raw echo signal of the ship target is processed by RD imaging algorithm, then the corresponding SAR simulated image is obtained. We select some ship targets to simulate SAR images, and then compare the simulated results with the real SAR images and the simulated results of the mainstream commercial simulation software to verify the effectiveness of the proposed method.
Authors
- Chuanxiang Cheng (ORCID: https://orcid.org/0009-0004-3485-4378)
- Junjie Li (ORCID: https://orcid.org/0000-0002-9274-9902)
- Ke Wu (ORCID: https://orcid.org/0009-0001-8568-6405)
- L. H. Wei
- Gaohao Zhu
Institutions
- PLA Information Engineering University (CN)
- Henan University of Urban Construction (CN)
- Henan Communication Science and Technology Research Institute (China) (CN)
- Yellow River Conservancy Technical Institute (CN)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3575702
- Citations
- 2
- Primary Topic
- Ocean Waves and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 3.59
Funders
- National Natural Science Foundation of China