University of Colorado System

Linear Kalman Filter Deep Dive (and Target Tracking)

University of Colorado System

Linear Kalman Filter Deep Dive (and Target Tracking)

This course is part of Applied Kalman Filtering Specialization

Gregory Plett

Instructor: Gregory Plett

Access provided by American University of Bahrain

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

26 assignments

Taught in English

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This course is part of the Applied Kalman Filtering Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

Knowing how to derive the steps of the Kalman filter is important for understanding the assumptions that are made and to be able to re-derive the steps for different assumptions. This week, you will learn how to derive the steps and will gain insight into how the Kalman filter works.

What's included

7 videos12 readings6 assignments1 discussion prompt

Last week, you learned the assumptions made when deriving the Kalman filter. What if these assumptions are not met correctly? What if numeric roundoff error causes failure? This week, you will learn how to solve problems with the standard Kalman filter.

What's included

7 videos7 readings7 assignments3 ungraded labs

The standard linear Kalman filter works well for state estimation, but can be extended to implement prediction and smoothing as well. Further, we can speed up the steps or even eliminate steps in some circumstances. This week, you will learn some extensions and refinements to linear Kalman filters.

What's included

7 videos7 readings7 assignments3 ungraded labs

A popular application of Kalman filters is to track (usually non-cooperating) targets. This week, you will learn how to implement standard and specialized Kalman filters suited for target tracking.

What's included

6 videos6 readings6 assignments2 ungraded labs

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Instructor

Gregory Plett
University of Colorado System
9 Courses 82,942 learners

Offered by

University of Colorado System

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