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.