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Linear Kalman Filter Deep Dive (and Target Tracking)

Master advanced Kalman filtering techniques with focus on derivation, implementation, and target tracking applications.

Master advanced Kalman filtering techniques with focus on derivation, implementation, and target tracking applications.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Applied Kalman Filtering Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

Instructors:

English

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Linear Kalman Filter Deep Dive (and Target Tracking)

This course includes

21 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Derive linear Kalman filter equations

  • Implement robust estimation algorithms

  • Develop prediction and smoothing methods

  • Design target tracking systems

  • Handle non-standard conditions

  • Optimize filter performance

Skills you'll gain

Kalman Filtering
Target Tracking
State Estimation
Linear Systems
Statistical Methods
Numerical Methods
System Modeling
Algorithm Implementation
Multiple Model Filtering
Signal Processing

This course includes:

7.8 Hours PreRecorded video

26 assignments

Access on Mobile, Tablet, Desktop

FullTime access

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There are 4 modules in this course

This comprehensive course provides a deep understanding of linear Kalman filter theory and implementation. Students learn to derive filter equations, handle non-standard conditions, and implement robust solutions. The curriculum covers advanced topics including prediction, smoothing, and multiple-model approaches, with practical applications in target tracking. Special attention is given to numerical robustness and handling of real-world challenges.

Deriving the linear Kalman filter

Module 1 · 5 Hours to complete

Making the linear Kalman filter bulletproof

Module 2 · 5 Hours to complete

Extensions and refinements to linear Kalman filters

Module 3 · 5 Hours to complete

Target-tracking application using a linear Kalman filter

Module 4 · 4 Hours to complete

Fee Structure

Instructor

Gregory Plett
Gregory Plett

5 rating

22 Reviews

72,282 Students

9 Courses

Leading Expert in Battery Systems and Control Engineering

Gregory Plett serves as Professor of Electrical and Computer Engineering at the University of Colorado Colorado Springs, where he has established himself as a pioneering researcher in battery management systems since 1998. His academic credentials include a B.Eng. from Carleton University and M.S.E.E. and Ph.D. degrees from Stanford University. His research focuses on advanced control systems for high-capacity batteries used in hybrid and electric vehicles, encompassing physics-based modeling, system identification, and state estimation. He has authored three influential volumes on Battery Management Systems, covering battery modeling, equivalent-circuit methods, and physics-based methods. As Director of the UCCS High-Capacity Battery Research and Test Laboratory, he leads cutting-edge research in battery pack simulation and management systems. His teaching portfolio includes advanced courses in control systems, battery dynamics, and management algorithms. A senior member of IEEE and life member of the Electrochemical Society, his work has significantly influenced the field of electric vehicle battery technology. His research innovations include developing methods for state-of-charge estimation, degradation modeling, and fast-charging protocols for battery packs.

Linear Kalman Filter Deep Dive (and Target Tracking)

This course includes

21 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.