--- name: RFInject authors: - Roberto Del Prete - Nermine Hendy license: APACHE-2.0 source: https://cdn-avatars.huggingface.co/v1/production/uploads/6538dbdcaca9fa108fd50595/2nTO6KAHh2UvbaJTa0jCs.png thumbnail: https://philab.esa.int/ --- # RFInject – Synthetic RFI Injection for Sentinel-1 SAR Data ## Overview RFInject is a research-grade Earth Observation dataset and methodology for controlled synthetic Radio Frequency Interference (RFI) injection into clean Sentinel-1 Synthetic Aperture Radar (SAR) data. The dataset is designed to enable reproducible benchmarking of RFI detection and mitigation algorithms, addressing a long-standing gap in the SAR community caused by the lack of standardized and controllable interference datasets. RFInject preserves the physical and statistical properties of real Sentinel-1 acquisitions while enabling full parametric control over injected interference characteristics. ## Motivation Radio Frequency Interference is a major source of performance degradation in modern SAR missions. Sentinel-1 data is particularly affected, yet most existing studies rely on ad-hoc or irreproducible contamination scenarios. RFInject enables: - Repeatable experimental setups - Controlled and parameterized interference scenarios - Algorithm-agnostic benchmarking across methods and sensors ## Dataset Structure ``` / ├── RFInject/ # Sentinel-1 data with injected synthetic RFI │ ├── product_001.zarr │ ├── product_002.zarr │ ├── product_003.zarr │ └── burst_0 │ └── burst_1 │ └── burst_2 │ └── zarr.json (the product metadata) │ └── echo (the clean burst) │ └── rfi (the rfi to add to burst) │ └── zarr.json (the RFI metadata) └── README.md ``` ## Data Characteristics | Property | Description | |---------------------|-------------| | Platform | Sentinel-1 | | Sensor | C-band SAR | | Data Level | L0 | | Interference Type | Synthetic RFI (parametric) | | File Format | zarr / analysis-ready | ## Methodology Synthetic RFI is injected by superimposing parameterized interference signals onto clean Sentinel-1 radar echoes. The approach ensures: - Spectral and temporal realism - Preservation of system characteristics - Full reproducibility through metadata-controlled parameters ## Ingestion with EOTDL ### CLI ```bash eotdl datasets get RFInject ``` ## Intended Use This dataset is intended for: - RFI detection and mitigation research - Machine learning model training and evaluation - Algorithm benchmarking - Reproducible SAR processing experiments Users are responsible for validating suitability for operational or safety-critical applications. ## Citation ``` @misc{rfinject_2025, author = { RFInject }, title = { v1 (Revision 23853e6) }, year = 2025, url = { https://huggingface.co/datasets/RFInject/v1 }, doi = { 10.57967/hf/7227 }, publisher = { Hugging Face } } ``` ## License This dataset is released under the APACHE-2.0 license. ## Acknowledgements Developed within the ESA Φ-lab research ecosystem and related collaborations.