Kalman Filter Boot Camp (and State Estimation)

Coursera MOOC / Non-credit USD 49

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Kalman Filter Boot Camp (and State Estimation)

About this course

Introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. Develops the background theoretical topics in state-space models and stochastic systems. Presents the steps of the linear Kalman filter and shows how to implement these steps in Octave code and how to evaluate the filter’s output.

What you'll learn

understand the concept of the Kalman filter
implement the Kalman filter in Octave
evaluate the output of the Kalman filter
grasp the principles of state-space models and stochastic systems

Course objectives

to introduce the Kalman filter as a solution for state estimation
to develop theoretical knowledge in stochastic systems
to provide hands-on experience with Octave coding

Skills you'll gain

data analysis control systems signal processing dynamic systems octave kalman filter state estimation state-space models stochastic systems

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