Localization and Mitigation Scheme for RFI in Dual-Channel SAR System Based on Alternating Constraints Optimization
Radio Frequency Interference (RFI) would lead to degradation of image quality for synthetic aperture radar (SAR) systems, resulting in a waste of observation resources. RFI source localization provides crucial prior information for RFI mitigation and spectrum management, and traditional RFI localization methods for multichannel SAR system suffer from localization ambiguity. This paper derives the RFI model for dual-channel SAR and investigates the mechanisms underlying localization ambiguity. A localization framework is proposed based on the varying characteristics of RFI with platform motion and the slant range difference model between dual-channels. This approach achieves localization by implementing mutual constraints among alternative optimization models. Moreover, an RFI filtering scheme is developed to facilitate the mutual cancellation of RFI between the two channels. The performance of the proposed method is validated using simulated RFI and real-measured RFI scenarios of Chinese Lutan-1 mission. The results indicate that the proposed method effectively mitigates the localization ambiguity, demonstrating high-precision localization performance. Moreover, it can reduce echo amplitude distortion and preserve degrees of freedom while removing RFI effectively.
Authors
- Jia Su (ORCID: https://orcid.org/0000-0003-0363-0625)
- Junli Chen (ORCID: https://orcid.org/0000-0002-3858-4844)
- Yanyang Liu (ORCID: https://orcid.org/0009-0002-6247-1134)
- Yuexian Wang (ORCID: https://orcid.org/0000-0002-3622-6162)
- Lei Cui (ORCID: https://orcid.org/0000-0003-4365-5173)
- Mingliang Tao (ORCID: https://orcid.org/0000-0002-0329-7124)
- Yifei Liu (ORCID: https://orcid.org/0009-0009-1098-8044)
Institutions
- Northwestern Polytechnical University (CN)
- Shanghai Micro Satellite Engineering Center (CN)
- Shanghai Academy of Spaceflight Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3596157
- Primary Topic
- Advanced SAR Imaging Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Shanghai Aerospace Science and Technology Innovation Foundation