RadarSim v1.0

Professional Pulse-Doppler Radar Simulation Platform
Physics-Based • AI-Enhanced • Open Source

Features • Quick Start • Shortcuts • Docs • Citation

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📖 Overview

RadarSim is a scientifically-validated radar simulation engine for education, research, and professional training. Built with NumPy/Numba for performance and PyQt6 for a modern UI.

Key Validation: Radar Equation calculations achieve ±0.005 dB accuracy vs. Skolnik reference values.

Figure 1: Main Plan Position Indicator (PPI) display showing detected targets.

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✨ Features

🎯 Physics Engine

Feature	Implementation	Reference
Radar Equation	Monostatic/Bistatic with Numba JIT	Skolnik, Ch. 2
Atmospheric Attenuation	ITU-R P.676-12 (O₂ + H₂O)	IEEE Std
Swerling RCS Models	Types 0-4 fluctuation	Swerling (1960)
Monopulse Tracking	Sum/Difference patterns, sub-beamwidth accuracy	Phase 20
3D Terrain Masking	4/3 Earth refraction, LOS shadowing	ITU-R P.526

🌪️ Environmental Effects

Feature	Details
Ground Clutter	Weibull distribution, σ⁰ coefficients
Sea Clutter	GIT Model, Douglas sea states (1-6)
Rain Physics	ITU-R P.838 Attenuation + Marshall-Palmer Clutter
MTI Filtering	Velocity threshold, slow-mover rejection

⚔️ Electronic Warfare

Technique	Type	Status
Noise Jamming	ECM	✅
DRFM Repeater	ECM	✅
RGPO/VGPO Deception	ECM	✅
Frequency Agility	ECCM	✅ New
Burn-Through Display	ECM Strobe	✅ New

📊 Visualization Scopes

Scope	Description
PPI	Plan Position Indicator with phosphor decay
B-Scope	Range vs Azimuth (AESA style) with ECM strobes
A-Scope	Amplitude vs Range with CFAR hover visualization
RHI	Range-Height Indicator (elevation)
3D Tactical	OpenGL terrain with target spheres
SAR Viewer	Real physics-based Synthetic Aperture Radar imaging

📸 Visualization Gallery

SAR Imaging	3D Tactical Map
Real-time SAR formation (Range-Doppler)	3D situation awareness

RHI Scope	A-Scope Analysis
Elevation scanning (Range-Height)	CFAR threshold visualization

📈 Analysis Tools

Tool	Function
Ambiguity Diagram	PRF vs Range/Velocity trade-off
ROC Curves	Pd vs Pfa for Swerling models
SNR Histogram	Detection strength distribution

📊 Analysis Tools

Ambiguity Diagram • ROC Curves • Real-time SNR Statistics

🤖 AI/ML Pipeline

• RandomForest Classifier trained on synthetic radar data
• Classes: Drone 🛸, Fighter Jet ✈️, Missile 🚀
• Real-time inference with confidence scoring

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🚀 Quick Start

# Clone repository
git clone https://github.com/SpaceEngineerSS/RadarSim.git
cd RadarSim

# Create virtual environment
python -m venv .venv
.venv\Scripts\activate  # Windows
# source .venv/bin/activate  # Linux/Mac

# Install dependencies
pip install -r requirements.txt

# Run application
python run_gui.py

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⌨️ Keyboard Shortcuts

Key	Action
Space	Play/Pause simulation
R	Reset (stop) simulation
1	Switch to PPI Scope
2	Switch to RHI Scope
3	Switch to 3D Tactical
4	Switch to 4th tab
F11	Toggle fullscreen
Ctrl+O	Load scenario
Ctrl+Shift+S	Save scenario
Ctrl+R	Start recording

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📁 Project Structure

RadarSim/
├── run_gui.py              # Main entry point
├── requirements.txt        # Dependencies
├── scenarios/              # YAML scenario files
│   ├── air_defense.yaml
│   ├── coastal.yaml
│   └── ...
├── src/
│   ├── physics/            # Core physics (radar_equation, clutter, ecm)
│   ├── signal/             # Signal processing (cfar, doppler, sar)
│   ├── tracking/           # Target tracking (kalman, monopulse)
│   ├── simulation/         # Simulation engine
│   ├── ui/                 # PyQt6 GUI components
│   ├── advanced/           # SAR/ISAR, Sensor Fusion, LPI
│   └── ml/                 # AI classification pipeline
├── models/                 # Trained ML models
├── docs/                   # Documentation
└── tests/                  # Unit tests

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📚 Documentation

Document	Description
Physics Engine	Radar equation, Monopulse, Ambiguity
Signal Processing	CFAR, MTI, SAR algorithms
User Guide	GUI walkthrough and Advanced features

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🔬 Scientific References

1. Skolnik, M.I. - Radar Handbook, 3rd Ed., McGraw-Hill, 2008
2. Richards, M.A. - Fundamentals of Radar Signal Processing, 2nd Ed., McGraw-Hill, 2014
3. IEEE Std 686-2017 - Radar Definitions
4. ITU-R P.676-12 - Attenuation by Atmospheric Gases
5. Cumming & Wong - Digital Processing of SAR Data, Artech House, 2005

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📜 License

MIT License - See LICENSE for details.

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📖 Citation

If you use RadarSim in academic work, please cite:

@software{radarsim2025,
  title = {RadarSim: Physics-Based Pulse-Doppler Radar Simulation},
  author = {RadarSim Contributors},
  year = {2025},
  url = {https://github.com/SpaceEngineerSS/RadarSim}
}

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👨‍💻 Developer

Mehmet Gümüş

• 🌐 Website: spacegumus.com.tr
• 🐙 GitHub: @SpaceEngineerSS

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