📡 RF Sensing Project

A hands-on project for exploring the core concepts of RF data processing using a Software Defined Radio (SDR). This project captures, processes, and visualizes real-time RF spectrum data to detect signals based on configurable thresholds.

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🧠 Purpose

This project is designed to help learners and developers understand:

• SDR configuration and data acquisition
• Signal processing fundamentals (FFT, windowing, power spectrum)
• Real-time signal detection
• Visualization of RF spectrum data

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📁 Project Structure

rf_sensing_project/
│
├── rf_sensing/                  # Main package
│   ├── __init__.py
│   ├── config.py                # Configuration constants
│   ├── sdr_interface.py         # SDR setup and teardown
│   ├── signal_processing.py     # Signal processing and detection logic
│   └── visualization.py         # Plotting and display logic
│
├── main.py                      # Entry point for the application
├── requirements.txt             # Dependencies
└── README.md                    # Project overview and usage

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⚙️ Configuration (config.py)

Key parameters for SDR and signal detection:

SDR_IP = "ip:192.168.2.1"
CENTER_FREQ = 2450e6
SAMPLE_RATE = 5e6
RX_LO = int(CENTER_FREQ)
RX_BUFFER_SIZE = 4 * 1024
GAIN_CONTROL_MODE = "slow_attack"
RX_GAIN_DB = 70
DETECTION_THRESHOLD_DB = -25

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🚀 How to Run

1. Install Dependencies

pip install -r requirements.txt

2. Connect Your SDR

Ensure your ADI Pluto SDR is connected and accessible at the configured IP address.

3. Run the Application

python main.py

Press Ctrl+C to stop the application.

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📊 What You’ll See

• A real-time plot of the RF spectrum
• Signal detection status based on a configurable threshold
• Visual feedback when a signal is detected

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🧩 Core Modules

• sdr_interface.py: Initializes and tears down the SDR connection.
• signal_processing.py: Applies FFT and detects signals based on power threshold.
• visualization.py: Displays the spectrum and detection status in real time.

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🛠️ Requirements

• Python 3.x
• ADI Pluto SDR
• Python packages:
  • numpy
  • matplotlib
  • adi (Analog Devices' SDR interface)

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📚 Learning Goals

• Understand how to interface with SDR hardware
• Learn basic RF signal processing techniques
• Visualize and interpret RF spectrum data
• Build a foundation for more advanced RF sensing applications