Devlog #2 – From Theory to Implementation

Project Progress

This session marked the transition from learning concepts to beginning the actual development of the Collision Risk Analysis Tool. I continued strengthening my Python skills while also applying orbital mechanics to real satellite data.

What I Worked On

• Completed one additional Python lesson to improve my understanding of programming concepts and syntax.
• Learned about Two-Line Element (TLE) data and how it is used to describe a satellite’s orbit.
• Studied the different parameters contained within a TLE and how they represent a satellite’s position and motion.
• Used TLE data to manually calculate the miss distance between satellites, helping me understand the mathematics behind conjunction analysis rather than relying on existing software.
• Began writing the first sections of code for the Collision Risk Analysis Tool, laying the foundation for future development.

Challenges

• Understanding the structure of TLE data required careful study, as each value represents a specific orbital parameter.
• Translating orbital calculations into code was more challenging than performing them manually, requiring additional planning before implementation.

What I Learned

• TLE data provides the essential orbital information needed for satellite tracking and conjunction analysis.
• Calculating miss distance manually gave me a much better understanding of how collision risk is determined.
• Writing software for orbital analysis requires both programming knowledge and a strong understanding of the underlying physics.

Next Goals

• Continue developing the Python codebase for the application.
• Automate the process of reading and interpreting TLE data.
• Implement calculations directly within the software instead of performing them manually.
• Begin testing the program with real satellite datasets to verify the accuracy of the calculations.
• Research methods for estimating collision probability once miss distance calculations are functioning correctly.

This session was an important milestone because it connected the theoretical concepts of orbital mechanics with practical software development. By combining Python programming with real TLE data and beginning the implementation of the tool, the project has now moved from the research phase into active development.

Devlog #1 – Collision Risk Analysis Tool

What I’m Building

I’m starting work on a Collision Risk Analysis Tool that aims to estimate the probability of collisions between objects in Earth orbit. The long-term goal is to use publicly available orbital data to analyze satellite trajectories, identify close approaches, and visualize potential collision risks in an easy-to-understand way.

What I Worked On

During this session, I focused on building the knowledge needed before starting development.

• Completed 4 introductory Python lessons to learn the fundamentals.

• Learned about:

  • Variables and data types
  • Loops and conditional statements
  • Functions
  • Basic input/output

• Began understanding the basics of orbital physics, including:

  • How satellites stay in orbit
  • Orbital altitude and velocity
  • Different types of Earth orbits (LEO, MEO, GEO)
  • Why orbital paths can intersect and create collision risks.

• Explored where real orbital data can be obtained and researched publicly available satellite datasets that can be used later in the project.

Challenges

• Understanding orbital mechanics was more difficult than expected because many concepts rely on physics and mathematics that are new to me.
• Finding reliable and usable orbital datasets required comparing multiple sources to determine which ones would be suitable for analysis.

What I Learned

• Python is much more approachable once the basic concepts are understood.
• Collision prediction depends heavily on accurate orbital data rather than just writing code.
• A strong understanding of orbital mechanics will be just as important as programming throughout this project.

Next Goals

• Continue learning Python and begin writing small practice programs.
• Learn how to read and process orbital datasets using Python.
• Research orbital elements (such as TLE data) and how they describe satellite orbits.
• Build a simple program to load satellite data and display basic information before moving on to collision analysis.
• Begin planning the overall architecture of the Collision Risk Analysis Tool.

Overall, this session was focused on building a solid foundation in both programming and orbital physics. Although no code for the final application has been written yet, the knowledge gained will make future development much more structured and efficient.