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Understanding Conceptual Filters and Numerical Considerations in Statistical Orbit Determination

This lecture by Professors Brandon A. Jones and George H. Born focuses on the comparison of conceptual filters and their numerical implications in statistical orbit determination. Key topics include information filters, linearization techniques, observation uncertainties, and the least squares batch method. The discussion also delves into sequential filtering methods like the Conventional Kalman Filter and the Extended Kalman Filter (EKF), emphasizing their conceptualization and covariance evolution. Students are reminded of upcoming homework deadlines and lecture quizzes.

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Understanding Conceptual Filters and Numerical Considerations in Statistical Orbit Determination

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  1. ASEN 5070: Statistical Orbit Determination I Fall 2013 Professor Brandon A. Jones Professor George H. Born Lecture 23: Conceptual Filter Comparison and Numeric Considerations

  2. Announcements • Homework 7 Due Friday • Lecture Quiz • Due by 5pm • In the coming weeks, we will start to bounce between topics in Chapters 4 and 5 • Information filter -> Square-root Information filter

  3. Conceptual Question

  4. Filter Conceptual Comparisons

  5. Filter Conceptualization • Linearization • Observation and Uncertainties

  6. Batch Filter Conceptualization • Least Squares (Batch)

  7. Batch Filter Conceptualization • Least Squares (Batch) • Replace reference trajectory with best-estimate • Update a priori state • Generate new computed observations Iterate a few times.

  8. Sequential Filter Conceptualization • Conventional Kalman

  9. Sequential Filter Conceptualization • Conventional Kalman

  10. Sequential Filter Conceptualization • Conventional Kalman

  11. Sequential Filter Conceptualization • Conventional Kalman

  12. Sequential Filter Conceptualization • Conventional Kalman

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  17. Sequential Filter Conceptualization • Conventional Kalman

  18. Sequential Filter Conceptualization • Conventional Kalman

  19. Sequential Filter Conceptualization • Conventional Kalman

  20. Sequential Filter Conceptualization • Conventional Kalman

  21. Sequential Filter Conceptualization • Conventional Kalman

  22. Sequential Filter Conceptualization • Conventional Kalman

  23. Sequential Filter Conceptualization • Conventional Kalman

  24. Sequential Filter Conceptualization • Conventional Kalman

  25. Sequential Filter Conceptualization • Conventional Kalman

  26. Sequential Filter Conceptualization • Conventional Kalman

  27. Sequential Filter Conceptualization • Conventional Kalman

  28. Sequential Filter Conceptualization • Conventional Kalman

  29. Sequential Filter Conceptualization • Conventional Kalman Evolution of covariance Mapping of final covariance

  30. Sequential Filter Conceptualization • EKF

  31. Sequential Filter Conceptualization • EKF

  32. Sequential Filter Conceptualization • EKF

  33. Sequential Filter Conceptualization • EKF

  34. Sequential Filter Conceptualization • EKF

  35. Sequential Filter Conceptualization • EKF

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  50. Sequential Filter Conceptualization • EKF

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