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Satellite Tracking and Trajectory Prediction Web Application (Earth Eye)

This web application enhances Space Situational Awareness (SSA) by providing real-time satellite tracking, trajectory prediction, and rocket launch simulation. It integrates traditional mathematical models and an experimental LSTM machine learning model for predictions, offering a user-friendly platform for researchers, professionals, and space enthusiasts.

Features

  • Satellite Tracking: Visualize satellite orbits in 3D using Three.js and Satellite.js.
  • Trajectory Prediction: Predict future satellite positions using SGP4 and LSTM models.
  • Rocket Launch Simulation: Simulate and visualize rocket trajectories based on user inputs and weather data.
  • Data Export: Download results in TXT, Excel, or TLE formats.

Technologies

  • Frontend: React, Three.js, React-Three-Fiber, Bootstrap
  • Backend: Flask, TensorFlow, NumPy, Skyfield
  • APIs: OpenWeatherMap, Space-Track

Setup

  1. Clone the repository:
    git clone [repository_url]  
  2. Install dependencies for the backend:
    pip install -r requirements.txt  
  3. Start the backend server:
    flask run  
  4. Navigate to the frontend directory, install dependencies, and start the React app:
    npm install  
    npm start  

Usage

  1. Navigate to the homepage.
  2. Use the Satellite Tracking tool for real-time tracking.
  3. Access Trajectory Prediction for specific satellites by NORAD ID.
  4. Run Rocket Launch Simulation with custom parameters.

Future Enhancements

  • Improved LSTM model accuracy with additional training data.
  • Real-time solar radiation pressure calculations.
  • Mobile responsiveness and performance optimization.