Space Traffic Management - AAE53300

March 24, 2026

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The class starts with learning how measurements are collected and processed and them moves on non-linear orbital motion and astrodynamics in the near-Earth realm. The focus is on orbit determination and orbit improvement to detect new objects and maintain custody of them. Lastly, the class focuses on determining the probability of collision of two resident space objects.

At the end of the course the students are equipped with a fundamental Matlab toolset to investigate their own STM or SSA problems.

Credit Hours: 3

Instructor(s): Carolin Frueh

Email: cfrueh@purdue.edu

Learning Objective: The course teaches the basic techniques and concepts relevant to Space Traffic Management (STM) and Space Situational Awareness (SSA) in the near-Earth realm from a rigorous engineering perspective.

Topics Covered:

  1. Two line elements and SGP4
  2. Sensors, CCD response in astrometric observations
  3. Influence of the optics in astrometric measurements
  4. Coordinate systems space fixed: right ascension, declination, geocentric, topocentric
  5. Coordinate systems Earth fixed: elevation, azimuth, aberration
  6. Coordinate systems: time systems, hour angle computation
  7. Coordinate systems: J2000, nutation and precession models simple and complex
  8. Initial orbit determination classical methods, Gauss, Herrick Gibbs etc.
  9. Initial orbit determination modern methods: admissible regions
  10. IOD: Admissible regions: connection of two regions
  11. First orbit improvement: least squares, introduction linear least squares
  12. First orbit improvement: least squares, non-linear least squares
  13. First orbit improvement: covariance discussion
  14. Orbit propagation: spherical expansion of the gravity field and pines implementation
  15. Orbit propagation: third body effects
  16. Orbit propagation: SRP and drag
  17. 2nd orbit improvement: Kalman filter as a test case
  18. 2nd orbit improvement: Extended Kalman filter in the orbit problem
  19. Probability of collision between two space objects and time of closest approach
  20. Covariance representation in non-linear dynamics, orbit improvement and orbit propagation

Prerequisites: Use of coding in Matlab or Python, undergraduate dynamics, undergraduate probability and statistics, Undergraduate orbital mechanics.

Applied / Theory: 10/90

Web Address: https://purdue.brightspace.com

Homework: Weekly homework

Projects: The final project consists of the parts of making a presentation video, and final report

The final project consists of the following elements: The selection of a relevant publication with respect to the topics of the class. The publication has to be shown to Prof. Frueh for approval prior to start working on the project. You cannot be an author or be mentioned in the acknowledgments of the selected paper. Results of the chosen publication are to be reproduced. A presentation has to be given consisting at minimum the following parts:

  1. Introduction to the topic
  2. Justification of the research
  3. Context of the publication and research content (other publications)
  4. Explanation of the methodology and results of the paper
  5. Comparison of your reproduced results with the results stated in the paper
  6. Your comments and observations on the research and the comparison
  7. Conclusions

Exams: No exam

Textbooks: Optional:

  • David Vallado, Fundamentals of Astrodynamics and Applications, Microcosm Press, 2013
  • Oliver Montenbruck, Satellite Orbits - Models, Methods and Applications, Springer, 2000
  • Bob Shultz, George Born, Byron Tapley, Statistical Orbit Determination, Academic Press, 2004

Computer Requirements: Latex compiler, Matlab or Python