📡 FMCW Radar Range Enhancement using Bistatic Geometry & Advanced Signal Processing

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🛰️ Project Overview

This project explores the development of an advanced FMCW Radar Simulation Framework capable of performing:

• 📡 Monostatic Radar Processing
• 🛰️ Bistatic Radar Geometry Modelling
• 📶 Range-Doppler Signal Processing
• 🧠 Advanced Range Enhancement Algorithms
• 🎯 CFAR-Based Target Detection
• 📊 SNR Benchmarking & Performance Evaluation
• 🔬 Weak Target Detection Analysis

The complete workflow was designed as a research-oriented radar processing pipeline where each phase gradually evolves from basic FMCW radar simulation into a fully enhanced bistatic radar evaluation system.

Unlike simplified academic implementations, this project focuses heavily on:

• realistic signal behaviour,
• geometry-aware processing,
• algorithm benchmarking,
• and performance visualization.

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🎥 Simulation Preview

FMCW radar simulation workflow with bistatic enhancement pipeline

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📌 Key Features

🚀 Core Functionalities

✅ FMCW Chirp Signal Generation
✅ Beat Signal Processing
✅ Range FFT Implementation
✅ Range-Doppler Mapping
✅ CA-CFAR Target Detection
✅ OS-CFAR Adaptive Detection
✅ Bistatic Radar Geometry
✅ Coherent Signal Integration
✅ Weak Target Detection Analysis
✅ SNR Benchmarking
✅ Coverage Mapping
✅ End-to-End Evaluation Dashboard

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🧠 Algorithms & Techniques Used

Category	Methods Implemented
Signal Processing	FFT, Zero-Padding, Windowing
Detection	CA-CFAR, OS-CFAR
Enhancement	Coherent Integration, SNR Boosting
Radar Geometry	Monostatic & Bistatic Models
Visualization	Heatmaps, Coverage Maps, Benchmark Graphs
Evaluation	ROC Curves, Detection Probability Analysis

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📊 Project Workflow

Phase 1 → FMCW Fundamentals & Environment Setup
Phase 2 → Monostatic Radar Baseline
Phase 3A → Bistatic Geometry Implementation
Phase 3B → Range Enhancement Algorithms
Phase 4 → Integrated Enhancement Framework
Phase 5 → Evaluation & Benchmarking

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🛰️ Radar System Architecture

The architecture combines:

• FMCW waveform generation
• Bistatic propagation modelling
• FFT-based signal processing
• CFAR target detection
• SNR enhancement techniques
• Final evaluation & benchmarking

This creates a complete research-oriented radar processing framework.

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📂 Repository Structure

FMCW-RADAR-PROJECT/
│
├── 📁 simulation files/
│   ├── P1/
│   ├── P2/
│   ├── P3A/
│   ├── P3B/
│   ├── P4/
│   └── P5/
│
├── 📁 images/
├── 📁 gifs/
├── 📁 plots/
├── 📁 results/
├── 📁 reports/
├── 📁 notebooks/
└── README.md

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📡 Phase-Wise Breakdown

🔹 Phase 1 — Fundamentals & Environment Setup

Objectives

• Understand FMCW radar principles
• Study chirp waveform behaviour
• Configure Python & MATLAB environment
• Explore RadarSimPy workflow
• Learn FFT-based range extraction

Major Outcomes

✅ Working radar simulation environment
✅ Understanding of beat signal generation
✅ FFT processing pipeline setup
✅ Initial waveform experiments

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🔹 Phase 2 — Monostatic FMCW Radar

Objectives

• Build monostatic FMCW radar pipeline
• Generate beat signals
• Implement range FFT
• Generate Range-Doppler maps
• Implement CA-CFAR detection

Major Outputs

✅ Range FFT plots
✅ Range-Doppler heatmaps
✅ CFAR detection results
✅ Baseline radar evaluation

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🔹 Phase 3A — Bistatic Geometry Modelling

Objectives

• Separate transmitter & receiver positions
• Implement bistatic range equations
• Analyze geometric effects
• Study baseline configurations

Major Outcomes

✅ Geometry-aware signal propagation
✅ Bistatic delay modelling
✅ Coverage enhancement observations
✅ Improved target observability

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🔹 Phase 3B — Range Enhancement Algorithms

Objectives

• Improve range resolution
• Increase weak target visibility
• Enhance SNR
• Implement adaptive detection methods

Algorithms Explored

✅ Zero-Padding FFT
✅ CA-CFAR
✅ OS-CFAR
✅ Coherent Integration
✅ Super-Resolution Concepts

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🔹 Phase 4 — Integrated Enhancement Framework

Objectives

• Combine bistatic geometry with enhancement algorithms
• Benchmark performance improvements
• Analyze SNR gain
• Evaluate target detection stability

Major Outputs

✅ Enhanced Range Maps
✅ SNR Benchmarking
✅ Detection Comparisons
✅ Integrated Evaluation Pipeline

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🔹 Phase 5 — Evaluation & Results

Objectives

• Compare monostatic vs bistatic performance
• Generate ROC curves
• Evaluate weak target detection
• Produce final benchmarking dashboard

Final Deliverables

✅ Coverage Maps
✅ ROC Curves
✅ Weak Target Detection Analysis
✅ Final Evaluation Dashboard
✅ Comparative Performance Study

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📷 Results & Visual Outputs

📊 Range-Doppler Processing

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🎯 CFAR Detection Analysis

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📶 Algorithm Benchmarking

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🛰️ Coverage Mapping

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📈 Weak Target Detection

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🧪 Final Evaluation Dashboard

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📊 Performance Highlights

Metric	Observation
Range Resolution	Improved using enhancement techniques
Detection Stability	Increased with CFAR-based methods
Weak Target Visibility	Improved through coherent integration
SNR Performance	Enhanced under bistatic configurations
Coverage Analysis	Better spatial diversity observed

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⚙️ Installation & Setup

1️⃣ Clone Repository

git clone https://github.com/Anshx-xx/FMCW-RADAR-PROJECT.git

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2️⃣ Install Dependencies

pip install numpy matplotlib scipy pandas

Optional:

pip install radarsimpy

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▶️ Running the Simulations

Execute Individual Phases

python simulation_files/P1/main.py
python simulation_files/P2/main.py
python simulation_files/P3A/main.py
python simulation_files/P3B/main.py
python simulation_files/P4/main.py
python simulation_files/P5/final_evaluation.py

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📚 Research Concepts Covered

• FMCW Radar Systems
• Bistatic Radar Geometry
• Signal Reflection Modelling
• Range FFT Processing
• Range-Doppler Mapping
• Adaptive Threshold Detection
• CFAR Algorithms
• SNR Enhancement
• Weak Target Detection
• Radar Performance Evaluation

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🚀 Future Improvements

Possible future extensions include:

• 🎯 Real-Time Radar Processing
• 🧠 AI-Based Target Classification
• 🛰️ MIMO Radar Integration
• ⚡ GPU-Accelerated Signal Processing
• 📡 Real Hardware Interfacing
• 🌍 Outdoor Clutter Modelling
• 🚁 Drone-Based Radar Platforms

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🤝 Contributions

Contributions, optimizations, and research suggestions are welcome.

Feel free to:

• Fork the repository
• Improve algorithms
• Add visualization modules
• Optimize FFT processing
• Experiment with alternative radar geometries

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👨‍💻 Author

Ansh Somaiya

📡 Radar Signal Processing Enthusiast
🛰️ FMCW Radar Simulation Research
💻 Python • MATLAB • Signal Processing

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⭐ Support The Project

If you found this repository useful:

⭐ Star the repository
🍴 Fork the project
📢 Share it with others interested in radar systems & signal processing

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📜 License

This project is intended for educational and research purposes.

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📡 Advanced FMCW Radar Processing • Bistatic Geometry • Signal Enhancement • Detection Intelligence 📡