131  Lesson 1.2.8: Where to from here?

Kalman Filter Boot Camp (and State Estimation)

This lesson summarizes the key concepts covered in the first week of the Kalman Filter Boot Camp and provides guidance on how to proceed with the specialization.
Probability and Statistics
Keywords

Kalman Filter, state estimation, linear algebra

131.1 Where to from here?

131.1.1 Summary of this week

  • How is the boot camp going? Are you getting stronger?
  • This week, you learned a lot of new concepts regarding state space models of dynamic systems.
  • You learned how they are defined, both for continuous-time and discrete-time systems.
    • You learned NCP, NCV, and CT example models that are useful for tracking.
    • You learned how to understand and simulate dynamic response.
    • You learned how to convert from a continuous-time to a discrete-time model.
    • You learned how to determine whether the system is observable, and why that matters.

131.1.2 Where to from here?

  • How is the boot camp going? Are you getting stronger?
  • This week, you learned a lot of new concepts regarding state-space models of dynamic systems.
  • You learned how they are defined, both for continuous-time and discrete-time systems.
    • You learned NCP, NCV, and CT example models that are useful for tracking.
    • You learned how to understand and simulate dynamic response.
    • You learned how to convert from a continuous-time to a discrete-time model.
    • You learned how to determine whether the system is observable, and why that matters.