Although the Kalman Filter is a simple concept, many educational resources present it through complex mathematical explanations and lack real-world examples or illustrations. This gives the impression that the topic is more complex than it actually is.

This guide presents an alternative approach that uses hands-on numerical examples and simple explanations to make the Kalman Filter easy to understand. It also includes examples with bad design scenarios where Kalman Filter fails to track the object correctly and discusses methods for correcting such issues.