Target Superresolution Reconstruction Approach for Bistatic Airborne Radar Based on Joint Convolution Echo Model
Bistatic airborne radar is widely studied because of its separated geometric configuration, offering flexible imaging ability for its receiver. However, when the bistatic platforms work in a synthetic aperture radar (SAR) mode, the bistatic system should obey strict imaging rules, including the geometric configuration and observation time. In this paper, a target superresolution reconstruction approach is proposed for a bistatic airborne radar system even if the imaging rules of bistatic SAR are not satisfied. On the one hand, a joint convolution echo (JCE) model for bistatic airborne radar is established by simultaneously modeling the echo amplitude and phase. The proposed JCE model can be applied to analyze the applicable boundary for bistatic airborne radar superresolution imaging. On the other hand, a vectored sparse iterative reweighted (VSIR) approach is proposed to reconstruct the targets for bistatic airborne radar system. Using the proposed JCE model and VSIR approach, high-resolution target imaging results can be obtained efficiently. Simulations are carried out to verify the performance of the proposed model and approach.
Authors
- Xinhao Chen (ORCID: https://orcid.org/0009-0007-7381-4127)
- Jiahao Shen
- Deqing Mao (ORCID: https://orcid.org/0000-0002-7408-1654)
- Lu Jiao (ORCID: https://orcid.org/0000-0002-0312-8830)
- Yin Zhang (ORCID: https://orcid.org/0000-0002-6761-2269)
- Yongchao Zhang (ORCID: https://orcid.org/0000-0001-5892-3391)
- Yongwei Zhang
- Yulin Huang
- Jianyu Yang
Institutions
- University of Electronic Science and Technology of China (CN)
- Yangtze University (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2026-08-25
- DOI
- https://doi.org/10.3390/rs18172873
- Primary Topic
- Advanced SAR Imaging Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Sichuan Province
- Fundamental Research Funds for the Central Universities