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README.md

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-Edit this `README.md` markdown file to author your organization card.
+# 🚀 RFInject: Synthetic RF Interference Injection for Sentinel-1 SAR L0 Data  
+
+## 📌 Motivation  
+- **Radio Frequency Interference (\gls{RFI})** is a **major source of performance degradation** in modern **Synthetic Aperture Radar (\gls{SAR})** missions.  
+- The **Copernicus Sentinel-1 constellation** is significantly affected, with numerous studies reporting its **detrimental impact**.  
+- However, the **lack of standardized and reproducible datasets** has so far **limited systematic benchmarking** of RFI detection and mitigation strategies.  
+
+---
+
+## 🛠️ What RFInject Brings  
+**RFInject** introduces a **methodology for controlled synthetic RFI injection** into clean Sentinel-1 L0 raw bursts, enabling:  
+- ✅ **Reproducible benchmarking** of mitigation algorithms  
+- ✅ **Realistic simulation** while retaining authentic system properties  
+- ✅ **Full parameter control** over RFI characteristics  
+
+---
+
+## 📐 Methodology Highlights  
+The framework is based on a **parametric signal model**:  
+- 🎯 **Synthetic RFI generation** by superimposing **modulated chirp trains** onto authentic Sentinel-1 radar echoes.  
+- 🧠 **Spectral and statistical fidelity** ensured to reflect real operational systems.  
+- 📊 **Metadata-rich parameter sets** controlling:  
+  - 📡 Waveform diversity  
+  - 🌍 Spatial extent  
+  - ⚡ Power scaling  
+
+---
+
+## 📂 Dataset Features  
+- **Clean Sentinel-1 L0 bursts** → contaminated with **controlled synthetic RFI**  
+- **Fully reproducible** contamination scenarios  
+- **Rich metadata** for systematic testing across **different algorithms** and **experimental setups**  
+
+---
+
+## 🎯 Impact and Applications  
+The dataset empowers researchers to:  
+- 🕵️‍♂️ **Detect** RFI more reliably  
+- 🛡️ **Mitigate** its impact effectively  
+- 🤖 Develop **learning-based solutions** for robust **RFI-resilient SAR processing pipelines**