Building a Real-Time Drone Detection System with Software-Defined Radio (SDR) скачать в хорошем качестве

Building a Real-Time Drone Detection System with Software-Defined Radio (SDR)

🚁 Detect, Track, and Localize Drones in Real-Time — using nothing but Python, SDR hardware, and machine learning! In this video, we dive deep into a production-grade, modular drone detection system built entirely in Python. Whether you're into cybersecurity, RF engineering, or AI-driven signal processing, this project showcases how to build a scalable, hardware-agnostic detection platform from the ground up. 🔍 What You’ll Learn: • How Software-Defined Radio (SDR) can be used to capture and analyze drone RF signals • Building a domain-driven, modular Python architecture for maintainability and scalability • Implementing multiple detection methods: energy-based, matched filtering, cyclostationary analysis, and ML-based detection • Real-time signal processing pipelines with FFT, filtering, demodulation, and feature extraction • Localization & tracking using DOA, TDOA, beamforming, and Kalman/Particle filters • Hardware abstraction for multi-device support (SDRs, antennas, GPS, power management) • ML model inference optimized for real-time performance with ONNX and hardware adaptation • REST, WebSocket, and gRPC APIs for integration and remote control • Visualization tools for spectrum analysis, 2D spatial mapping, and track history • Comprehensive testing suite including unit, integration, performance, and field tests • Deployment-ready with Docker, CI/CD, configuration management, and monitoring 🛠 Tech Stack: • Python 3.10+ • NumPy, SciPy, scikit-learn, TensorFlow/PyTorch • GNU Radio, SoapySDR, PyLMS • FastAPI, WebSockets, gRPC • SQLAlchemy, SQLite/PostgreSQL • Matplotlib, Plotly • Pytest, DVC, Docker, Makefile • GitHub Actions 📂 Project Structure Highlights: • src/ – Clean, domain-separated modules (hardware, processing, detection, ML, runtime, visualization, API, database) • tests/ – Full test pyramid with mocks, unit, integration, performance, and field tests • config/, deployment/, models/, notebooks/ – Supporting directories for end-to-end workflow • requirements.txt, pyproject.toml, Dockerfile – Production-ready dependency and build management 🎯 Who Is This For? • RF Engineers & SDR Enthusiasts • Python Developers interested in real-time systems • AI/ML Engineers working on signal classification • Cybersecurity professionals exploring physical layer security • Students & researchers in communications and drone technology